ECJ clarifies Database Directive scope in screen scraping case

EC on the legal protection of databases (Database Directive) in a case concerning the extraction of data from a third party’s website by means of automated systems or software for commercial purposes (so called 'screen scraping').

Flight data extracted

The case, Ryanair Ltd vs. PR Aviation BV, C-30/14, is of interest to a range of companies such as price comparison websites. It stemmed from  Dutch company PR Aviation operation of a website where consumers can search through flight data of low-cost airlines  (including Ryanair), compare prices and, on payment of a commission, book a flight. The relevant flight data is extracted from third-parties’ websites by means of ‘screen scraping’ practices.

Ryanair claimed that PR Aviation’s activity:

• amounted to infringement of copyright (relating to the structure and architecture of the database) and of the so-called sui generis database right (i.e. the right granted to the ‘maker’ of the database where certain investments have been made to obtain, verify, or present the contents of a database) under the Netherlands law implementing the Database Directive;

• constituted breach of contract. In this respect, Ryanair claimed that a contract existed with PR Aviation for the use of its website. Access to the latter requires acceptance, by clicking a box, of the airline’s general terms and conditions which, amongst others, prohibit unauthorized ‘screen scraping’ practices for commercial purposes.

Ryanair asked Dutch courts to prohibit the infringement and order damages. In recent years the company has been engaged in several legal cases against web scrapers across Europe.

The Local Court, Utrecht, and the Court of Appeals of Amsterdam dismissed Ryanair’s claims on different grounds. The Court of Appeals, in particular, cited PR Aviation’s screen scraping of Ryanair’s website as amounting to a “normal use” of said website within the meaning of the lawful user exceptions under Sections 6 and 8 of the Database Directive, which cannot be derogated by contract (Section 15).

Ryanair appealed

Ryanair appealed the decision before the Netherlands Supreme Court (Hoge Raad der Nederlanden), which decided to refer the following question to the ECJ for a preliminary ruling: “Does the application of [Directive 96/9] also extend to online databases which are not protected by copyright on the basis of Chapter II of said directive or by a sui generis right on the basis of Chapter III, in the sense that the freedom to use such databases through the (whether or not analogous) application of Article[s] 6(1) and 8, in conjunction with Article 15 [of Directive 96/9] may not be limited contractually?.”

The ECJ’s ruling

The ECJ (without the need of the opinion of the advocate general) ruled that the Database Directive is not applicable to databases which are not protected either by copyright or by the sui generis database right. Therefore, exceptions to restricted acts set forth by Sections 6 and 8 of the Directive do not prevent the database owner from establishing contractual limitations on its use by third parties. In other words, restrictions to the freedom to contract set forth by the Database Directive do not apply in cases of unprotected databases. Whether Ryanair’s website may be entitled to copyright or sui generis database right protection needs to be determined by the competent national court.

The ECJ’s decision is not particularly striking from a legal standpoint. Yet, it could have a significant impact on the business model of price comparison websites, aggregators, and similar businesses. Owners of databases that could not rely on intellectual property protection may contractually prevent extraction and use (“scraping”) of content from their online databases. Thus, unprotected databases could receive greater protection than the one granted by IP law.

Antitrust implications

However, the lawfulness of contractual restrictions prohibiting access and reuse of data through screen scraping practices should be assessed under an antitrust perspective. In this respect, in 2013 the Court of Milan ruled that Ryanair’s refusal to grant access to its database to the online travel agency Viaggiare S.r.l. amounted to an abuse of dominant position in the downstream market of information and intermediation on flights (decision of June 4, 2013 Viaggiare S.r.l. vs Ryanair Ltd). Indeed, a balance should be struck between the need to compensate the efforts and investments made by the creator of the database with the interest of third parties to be granted with access to information (especially in those cases where the latter are not entitled to copyright protection).

Additionally, web scraping triggers other issues which have not been considered by the ECJ’s ruling. These include, but are not limited to trademark law (i.e., whether the use of a company’s names/logos by the web scraper without consent may amount to trademark infringement), data protection (e.g., in case the scraping involves personal data), or unfair competition.

Source: http://www.globallegalpost.com/blogs/global-view/ecj-clarifies-database-directive-scope-in-screen-scraping-case-128701/

Data Scraping - What Are Hand-Scraped Hardwood Floors and What Are the Benefits?

If you love the look of hardwood flooring with lots of character, then you may want to check out hand-scraped hardwood flooring. Hand-scraped wood provides a warm vintage look, providing the floor instant character. These types of scraped hardwoods are suitable for living rooms, dining rooms, hallways and bedrooms. But what exactly is hand-scraped hardwood flooring?

Well, it is literally what you think it is. Hand-scraped hardwood flooring is created by hand using specialized wood working tools to make each board unique and giving an overall "old worn" appearance.

At Innovation Builders we offer solid wood floors finished on site with an actual hand-scraping technique followed by stain and sealer. Solid wood floors are installed by an expert team of technicians who work each board with skilled craftsman-like attention to detail. Following the scraping procedure the floor is stained by hand with a customer selected stain color, and then protected with multiple coats of sealing and finishing polyurethane. This finishing process of staining, sealing and coating the wood floors contributes to providing the look and durability of an old reclaimed wood floor, but with today's tough, urethane finishes.

There are many, many benefits to hand-scraped wood flooring. Overall, these floors are extremely durable and hard wearing, providing years of trouble-free use. These wood floors remain looking newer for longer because the texture that the process provides hides the typical dents, dings and scratches that other floors can't hide so easily. That's great news for households with kids, dogs, and cats.

These types of wood flooring have another unique advantage as well. When you do scratch these floors during their lifetime, the scratches are easily repaired. As long as the scratch isn't too deep you can make them practically disappear without ever having to hire a professional. It's simple to hide the scratch by using a color-matched stain marker or repair kit that is readily available through local flooring distributors. These features make hand-scraped hardwood flooring a lot more durable and hassle-free to maintain than other types of wood flooring.

The expert processes utilized in the creation of these floors provides a custom look of worn wood with deep color and subtle highlights. When the light hits the wood at different times during the day, it provides an understated but powerful effect of depth and beauty. They instantly offer your rooms a rustic look full of character, allowing your home to become a warm and inviting environment. The rustic look of this wood provides a texture, style and rustic appeal that cannot be matched by any other type of flooring.

Hand-Scraped Hardwood Flooring is a floor that says welcome and adds a touch of elegance to any home. If you are looking to buy a new home and you haven't had the opportunity to see or feel hand scraped hardwoods, stop in any of the model homes at Innovation Builders in Keller, North Richland Hills or Grand Prairie, Texas and check it out!

Source: http://ezinearticles.com/?What-Are-Hand-Scraped-Hardwood-Floors-and-What-Are-the-Benefits?&id=6026646

Web scraping in under 60 seconds: the magic of import.io

Import.io is a very powerful and easy-to-use tool for data extraction that has the aim of getting data from any website in a structured way. It is meant for non-programmers that need data (and for programmers who don’t want to overcomplicate their lives).

I almost forgot!! Apart from everything, it is also a free tool (o_O)

The purpose of this post is to teach you how to scrape a website and make a dataset and/or API in under 60 seconds. Are you ready?

It’s very simple. You just have to go to http://magic.import.io; post the URL of the site you want to scrape, and push the “GET DATA” button. Yes! It is that simple! No plugins, downloads, previous knowledge or registration are necessary. You can do this from any browser; it even works on tablets and smartphones.

For example: if we want to have a table with the information on all items related to Chewbacca on MercadoLibre (a Latin American version of eBay), we just need to go to that site and make a search – then copy and paste the link (http://listado.mercadolibre.com.mx/chewbacca) on Import.io, and push the “GET DATA” button.

You’ll notice that now you have all the information on a table, and all you need to do is remove the columns you don’t need. To do this, just place the mouse pointer on top of the column you want to delete, and an “X” will appear.

Good news for those of us who are a bit more technically-oriented! There is a button that says “GET API” and this one is good to, well, generate an API that will update the data on each request. For this you need to create an account (which is also free of cost).

As you saw, we can scrape any website in under 60 seconds, even if it includes tons of results pages. This truly is magic, no? For more complex things that require logins, entering subwebs, automatized searches, et cetera, there is downloadable import.io software… But I’ll explain that in a different post.

Source: http://schoolofdata.org/2014/12/09/web-scraping-in-under-60-seconds-the-magic-of-import-io/

Scraping Services - Assuring Scraping Success with Proxy Data Scraping

Have you ever heard of "Data Scraping?" Data Scraping is the process of collecting useful data that has been placed in the public domain of the internet (private areas too if conditions are met) and storing it in databases or spreadsheets for later use in various applications. Data Scraping technology is not new and many a successful businessman has made his fortune by taking advantage of data scraping technology.

Sometimes website owners may not derive much pleasure from automated harvesting of their data. Webmasters have learned to disallow web scrapers access to their websites by using tools or methods that block certain ip addresses from retrieving website content. Data scrapers are left with the choice to either target a different website, or to move the harvesting script from computer to computer using a different IP address each time and extract as much data as possible until all of the scraper's computers are eventually blocked.

Thankfully there is a modern solution to this problem. Proxy Data Scraping technology solves the problem by using proxy IP addresses. Every time your data scraping program executes an extraction from a website, the website thinks it is coming from a different IP address. To the website owner, proxy data scraping simply looks like a short period of increased traffic from all around the world. They have very limited and tedious ways of blocking such a script but more importantly -- most of the time, they simply won't know they are being scraped.

You may now be asking yourself, "Where can I get Proxy Data Scraping Technology for my project?" The "do-it-yourself" solution is, rather unfortunately, not simple at all. Setting up a proxy data scraping network takes a lot of time and requires that you either own a bunch of IP addresses and suitable servers to be used as proxies, not to mention the IT guru you need to get everything configured properly. You could consider renting proxy servers from select hosting providers, but that option tends to be quite pricey but arguably better than the alternative: dangerous and unreliable (but free) public proxy servers.

There are literally thousands of free proxy servers located around the globe that are simple enough to use. The trick however is finding them. Many sites list hundreds of servers, but locating one that is working, open, and supports the type of protocols you need can be a lesson in persistence, trial, and error. However if you do succeed in discovering a pool of working public proxies, there are still inherent dangers of using them. First off, you don't know who the server belongs to or what activities are going on elsewhere on the server. Sending sensitive requests or data through a public proxy is a bad idea. It is fairly easy for a proxy server to capture any information you send through it or that it sends back to you. If you choose the public proxy method, make sure you never send any transaction through that might compromise you or anyone else in case disreputable people are made aware of the data.

A less risky scenario for proxy data scraping is to rent a rotating proxy connection that cycles through a large number of private IP addresses. There are several of these companies available that claim to delete all web traffic logs which allows you to anonymously harvest the web with minimal threat of reprisal. Companies such as offer large scale anonymous proxy solutions, but often carry a fairly hefty setup fee to get you going.

The other advantage is that companies who own such networks can often help you design and implementation of a custom proxy data scraping program instead of trying to work with a generic scraping bot. After performing a simple Google search, I quickly found one company (www.ScrapeGoat.com) that provides anonymous proxy server access for data scraping purposes. Or, according to their website, if you want to make your life even easier, ScrapeGoat can extract the data for you and deliver it in a variety of different formats often before you could even finish configuring your off the shelf data scraping program.

Whichever path you choose for your proxy data scraping needs, don't let a few simple tricks thwart you from accessing all the wonderful information stored on the world wide web!

Source: http://ezinearticles.com/?Assuring-Scraping-Success-with-Proxy-Data-Scraping&id=248993

Getting Data from the Web Scraping

You’ve tried everything else, and you haven’t managed to get your hands on the data you want. You’ve found the data on the web, but, alas — no download options are available and copy-paste has failed you. Fear not, there may still be a way to get the data out. For example you can:

•    Get data from web-based APIs, such as interfaces provided by online databases and many modern web applications (including Twitter, Facebook and many others). This is a fantastic way to access government or commercial data, as well as data from social media sites.

•    Extract data from PDFs. This is very difficult, as PDF is a language for printers and does not retain much information on the structure of the data that is displayed within a document. Extracting information from PDFs is beyond the scope of this book, but there are some tools and tutorials that may help you do it.

•    Screen scrape web sites. During screen scraping, you’re extracting structured content from a normal web page with the help of a scraping utility or by writing a small piece of code. While this method is very powerful and can be used in many places, it requires a bit of understanding about how the web works.

With all those great technical options, don’t forget the simple options: often it is worth to spend some time searching for a file with machine-readable data or to call the institution which is holding the data you want.

In this chapter we walk through a very basic example of scraping data from an HTML web page.

What is machine-readable data?

The goal for most of these methods is to get access to machine-readable data. Machine readable data is created for processing by a computer, instead of the presentation to a human user. The structure of such data relates to contained information, and not the way it is displayed eventually. Examples of easily machine-readable formats include CSV, XML, JSON and Excel files, while formats like Word documents, HTML pages and PDF files are more concerned with the visual layout of the information. PDF for example is a language which talks directly to your printer, it’s concerned with position of lines and dots on a page, rather than distinguishable characters.

Scraping web sites: what for?

Everyone has done this: you go to a web site, see an interesting table and try to copy it over to Excel so you can add some numbers up or store it for later. Yet this often does not really work, or the information you want is spread across a large number of web sites. Copying by hand can quickly become very tedious, so it makes sense to use a bit of code to do it.

The advantage of scraping is that you can do it with virtually any web site — from weather forecasts to government spending, even if that site does not have an API for raw data access.

What you can and cannot scrape

There are, of course, limits to what can be scraped. Some factors that make it harder to scrape a site include:

•    Badly formatted HTML code with little or no structural information e.g. older government websites.

•    Authentication systems that are supposed to prevent automatic access e.g. CAPTCHA codes and paywalls.

•    Session-based systems that use browser cookies to keep track of what the user has been doing.

•    A lack of complete item listings and possibilities for wildcard search.

•    Blocking of bulk access by the server administrators.

Another set of limitations are legal barriers: some countries recognize database rights, which may limit your right to re-use information that has been published online. Sometimes, you can choose to ignore the license and do it anyway — depending on your jurisdiction, you may have special rights as a journalist. Scraping freely available Government data should be fine, but you may wish to double check before you publish. Commercial organizations — and certain NGOs — react with less tolerance and may try to claim that you’re “sabotaging” their systems. Other information may infringe the privacy of individuals and thereby violate data privacy laws or professional ethics.

Tools that help you scrape

There are many programs that can be used to extract bulk information from a web site, including browser extensions and some web services. Depending on your browser, tools like Readability (which helps extract text from a page) or DownThemAll (which allows you to download many files at once) will help you automate some tedious tasks, while Chrome’s Scraper extension was explicitly built to extract tables from web sites. Developer extensions like FireBug (for Firefox, the same thing is already included in Chrome, Safari and IE) let you track exactly how a web site is structured and what communications happen between your browser and the server.

ScraperWiki is a web site that allows you to code scrapers in a number of different programming languages, including Python, Ruby and PHP. If you want to get started with scraping without the hassle of setting up a programming environment on your computer, this is the way to go. Other web services, such as Google Spreadsheets and Yahoo! Pipes also allow you to perform some extraction from other web sites.

How does a web scraper work?

Web scrapers are usually small pieces of code written in a programming language such as Python, Ruby or PHP. Choosing the right language is largely a question of which community you have access to: if there is someone in your newsroom or city already working with one of these languages, then it makes sense to adopt the same language.

While some of the click-and-point scraping tools mentioned before may be helpful to get started, the real complexity involved in scraping a web site is in addressing the right pages and the right elements within these pages to extract the desired information. These tasks aren’t about programming, but understanding the structure of the web site and database.

When displaying a web site, your browser will almost always make use of two technologies: HTTP is a way for it to communicate with the server and to request specific resource, such as documents, images or videos. HTML is the language in which web sites are composed.

The anatomy of a web page

Any HTML page is structured as a hierarchy of boxes (which are defined by HTML “tags”). A large box will contain many smaller ones — for example a table that has many smaller divisions: rows and cells. There are many types of tags that perform different functions — some produce boxes, others tables, images or links. Tags can also have additional properties (e.g. they can be unique identifiers) and can belong to groups called ‘classes’, which makes it possible to target and capture individual elements within a document. Selecting the appropriate elements this way and extracting their content is the key to writing a scraper.

Viewing the elements in a web page: everything can be broken up into boxes within boxes.

To scrape web pages, you’ll need to learn a bit about the different types of elements that can be in an HTML document. For example, the <table> element wraps a whole table, which has <tr> (table row) elements for its rows, which in turn contain <td> (table data) for each cell. The most common element type you will encounter is <div>, which can basically mean any block of content. The easiest way to get a feel for these elements is by using the developer toolbar in your browser: they will allow you to hover over any part of a web page and see what the underlying code is.

Tags work like book ends, marking the start and the end of a unit. For example <em> signifies the start of an italicized or emphasized piece of text and </em> signifies the end of that section. Easy.

Figure 57. The International Atomic Energy Agency’s (IAEA) portal (news.iaea.org)

An example: scraping nuclear incidents with Python

NEWS is the International Atomic Energy Agency’s (IAEA) portal on world-wide radiation incidents (and a strong contender for membership in the Weird Title Club!). The web page lists incidents in a simple, blog-like site that can be easily scraped.

To start, create a new Python scraper on ScraperWiki and you will be presented with a text area that is mostly empty, except for some scaffolding code. In another browser window, open the IAEA site and open the developer toolbar in your browser. In the “Elements” view, try to find the HTML element for one of the news item titles. Your browser’s developer toolbar helps you connect elements on the web page with the underlying HTML code.

Investigating this page will reveal that the titles are <h4> elements within a <table>. Each event is a <tr> row, which also contains a description and a date. If we want to extract the titles of all events, we should find a way to select each row in the table sequentially, while fetching all the text within the title elements.

In order to turn this process into code, we need to make ourselves aware of all the steps involved. To get a feeling for the kind of steps required, let’s play a simple game: In your ScraperWiki window, try to write up individual instructions for yourself, for each thing you are going to do while writing this scraper, like steps in a recipe (prefix each line with a hash sign to tell Python that this not real computer code). For example:

# Look for all rows in the table

# Unicorn must not overflow on left side.

Try to be as precise as you can and don’t assume that the program knows anything about the page you’re attempting to scrape.

Once you’ve written down some pseudo-code, let’s compare this to the essential code for our first scraper:

import scraperwiki

In this first section, we’re importing existing functionality from libraries — snippets of pre-written code. scraperwiki will give us the ability to download web sites, while lxml is a tool for the structured analysis of HTML documents. Good news: if you are writing a Python scraper with ScraperWiki, these two lines will always be the same.

doc_text = scraperwiki.scrape(url)

doc = html.fromstring(doc_text)

Next, the code makes a name (variable): url, and assigns the URL of the IAEA page as its value. This tells the scraper that this thing exists and we want to pay attention to it. Note that the URL itself is in quotes as it is not part of the program code but a string, a sequence of characters.

We then use the url variable as input to a function, scraperwiki.scrape. A function will provide some defined job — in this case it’ll download a web page. When it’s finished, it’ll assign its output to another variable, doc_text. doc_text will now hold the actual text of the website — not the visual form you see in your browser, but the source code, including all the tags. Since this form is not very easy to parse, we’ll use another function, html.fromstring, to generate a special representation where we can easily address elements, the so-called document object model (DOM).

In this final step, we use the DOM to find each row in our table and extract the event’s title from its header. Two new concepts are used: the for loop and element selection (.cssselect). The for loop essentially does what its name implies; it will traverse a list of items, assigning each a temporary alias (row in this case) and then run any indented instructions for each item.

The other new concept, element selection, is making use of a special language to find elements in the document. CSS selectors are normally used to add layout information to HTML elements and can be used to precisely pick an element out of a page. In this case (Line. 6) we’re selecting #tblEvents tr which will match each <tr> within the table element with the ID tblEvents (the hash simply signifies ID). Note that this will return a list of <tr> elements.

As can be seen on the next line (Line. 7), where we’re applying another selector to find any <a> (which is a hyperlink) within a <h4> (a title). Here we only want to look at a single element (there’s just one title per row), so we have to pop it off the top of the list returned by our selector with the .pop() function.

Note that some elements in the DOM contain actual text, i.e. text that is not part of any markup language, which we can access using the [element].text syntax seen on line 8. Finally, in line 9, we’re printing that text to the ScraperWiki console. If you hit run in your scraper, the smaller window should now start listing the event’s names from the IAEA web site.

You can now see a basic scraper operating: it downloads the web page, transforms it into the DOM form and then allows you to pick and extract certain content. Given this skeleton, you can try and solve some of the remaining problems using the ScraperWiki and Python documentation:

•    Can you find the address for the link in each event’s title?

•    Can you select the small box that contains the date and place by using its CSS class name and extract the element’s text?

•    ScraperWiki offers a small database to each scraper so you can store the results; copy the relevant example from their docs and adapt it so it will save the event titles, links and dates.

•    The event list has many pages; can you scrape multiple pages to get historic events as well?

As you’re trying to solve these challenges, have a look around ScraperWiki: there are many useful examples in the existing scrapers — and quite often, the data is pretty exciting, too. This way, you don’t need to start off your scraper from scratch: just choose one that is similar, fork it and adapt to your problem.

Source: http://datajournalismhandbook.org/1.0/en/getting_data_3.html

Data Scraping Services - Login to Website Programmatically using C# for Web Scraping

In many scenario the data is available after login that you want to scrape. So to reach at the page where data is located you need to implement code in web scraper  that automatically takes usename/email and password to login into website, once login is done you can do crawling and parsing as required.

Many third party web scraping application provides functionality where you can locate login url and set login parameters and that login task will be called when scraper start and do web scraping.

Below is C# example of programmatically  login to demo login page

http://demo.webdata-scraping.com/login.php

Below is HTML code of Login form:

<form class="form-signin" id="login" method="post" role="form"> <h3 class="form-signin-heading">Please sign in</h3> <a href="#" id="flipToRecover" class="flipLink"> <div id="triangle-topright"></div> </a> <input type="email" class="form-control" name="loginEmail" id="loginEmail" placeholder="Email address" required autofocus> <input type="password" class="form-control" name="loginPass" id="loginPass" placeholder="Password" required> <button class="btn btn-lg btn-primary btn-block" name="login_submit" id="login_submit" type="submit">Sign in</button> </form>

<form class="form-signin" id="login" method="post" role="form">

            <h3 class="form-signin-heading">Please sign in</h3>

            <a href="#" id="flipToRecover" class="flipLink">

              <div id="triangle-topright"></div>

            </a>

            <input type="email" class="form-control" name="loginEmail" id="loginEmail" placeholder="Email address" required autofocus>

            <input type="password" class="form-control" name="loginPass" id="loginPass" placeholder="Password" required>

            <button class="btn btn-lg btn-primary btn-block" name="login_submit" id="login_submit" type="submit">Sign in</button>

</form>

In this code you can notice there is ID for email input box that is id=”loginEmail”  and password input box that is id=”loginPass”

so by taking this ID we will use below two method of webBrowser control and fill the value of each input box using following code

webBrowser1.Document.GetElementById("loginEmail").InnerText =textBox1.Text.ToString(); webBrowser1.Document.GetElementById("loginPass").InnerText = textBox2.Text.ToString();

webBrowser1.Document.GetElementById("loginEmail").InnerText =textBox1.Text.ToString();

webBrowser1.Document.GetElementById("loginPass").InnerText = textBox2.Text.ToString();

After the value filled to Email and Password input box we will just call click event of submit button which is named as Sign In

webBrowser1.Document.GetElementById("login_submit").InvokeMember("click");

webBrowser1.Document.GetElementById("login_submit").InvokeMember("click");

So this is very basic example how you can login to website programatically when you need to access data that is available after login to website.  This is very simple way in which you can work with Web Browser control but there are some other way as well using which you can do same thing.

Source: http://webdata-scraping.com/login-website-programmatically-using-c-web-scraping/

Data Extraction Services

Are you finding it tedious to perform your routine tasks as well as finding time to research for some information? Don't worry; all you have to do is outsource data extraction requirements to reliable service providers such as Hi-Tech BPO Services.

We can assist you in finding, extracting, gathering, processing and validating all the required data through our effective data extraction services. We can extract data from any given source such as websites, databases, printed documents, directories, etc.

With a whole plethora of data extraction services solutions; we are definitely a one stop solution to all your data extraction services requirements.

For utilizing our data extraction services, all you have to do is outsource data extraction requirements to us, and we will create effective strategies and extract the required data from all preferred sources. Then we will arrange all the extracted data in a systematic order.

Types of data extraction services provided by our data extraction India unit:

The data extraction India unit of Hi-Tech BPO Services can attend to all types of outsource data extraction requirements. Following are just some of the data extraction services we have delivered:

•    Data extraction from websites
•    Data extraction from databases
•    Extraction of data from directories
•    Extracting data from books
•    Data extraction from forms
•    Extracting data from printed materials

Features of Our Data Extraction Services:

•    Reliable collection of resources for data extraction
•    Extensive range of data extraction services
•    Data can be extracted from any available source be it a digital source or a hard copy source
•    Proper researching, extraction, gathering, processing and validation of data
•    Reasonably priced data extraction services
•    Quality and confidentiality ensured through various strict measures

Our data extraction India unit has the competency to handle any of your data extraction services requirements. Just provide us with your specific requirements and we will extract data accordingly from your preferred resources, if particularly specified. Otherwise we will completely rely on our collection of resources for extracting data for you.

Source: http://www.hitechbposervices.com/data-extraction.php

Data Scraping - One application or multiple?

I have 30+ sources of data I scrape daily in various formats (xml, html, csv). Over the last three years Ive built 20 or so c# console applications that go out, download the data and re-format it into a database. But Im curious what other people are doing for this type of task. Are people building one tool that has a lot of variables and inputs or are people designing 20+ programs to scrape and parse this data. Everything is hard-coded into each console and run through Windows Task Manager.

Added a couple additional thoughts/details:

    Of the 30 sources, they all have unique properties, all are uploaded into individual MySQL tables and all have varying frequencies. For example, one data source is hit once a minute, another on 5 minute intervals. Majority are once an hour and once a day.

At current I download the formats (xml, csv, html), parse them into a formatted csv and put them into staging folders. Within that folder, I run an application that reads a config file specific to the folder. When a new csv is added to the folder, the application then uploads the data into the specific MySQL tables designated in the config file.

Im wondering if it is worth re-building all this into a larger complex program that is more capable of dynamically adding content+scrapes and adjusting to format changes.

Looking for outside thoughts.

5 Answers

What you are working on is basically ETL. So at a high level you need an export component (get stuff) a transform component (map to known format) and a load (take known format and put stuff somewhere). If you are comfortable being tied to a RDBMS you could use something like SQL Server SSIS packages. What I would do is create a host application that managed common aspects of the overall process (errors, and pipeline processing). Then make the specifics of the E, T, and L pluggable. A low ceremony way to get this would be to host the powershell runtime and create each seesion with common context objects that the scripts will use to communicate. You get a built in pipe and filter model for scripts and easy, safe extensibility. This design has worked extremely for my team with a similar situation.

Resist the temptation to rewrite.

However, for new code, you could plan for what you know has already happened. Write a retrieval mechanism that you can reuse through configuration. Write a translation mechanism that you can reuse (maybe in a library that you can call with very little code). Write a saving mechanism that can be called or configured.

At this point, you've written #21(+). Now, the following ones can be handled with a tiny bit of code and configuration. Yay!

(You may want to implement this in a service that handles multiple conversions, but weight the benefits of it versus the ability to separate errors in one module from the rest.)

1

It depends - if you need the scrapers to feed into a single application/database and have a uniform data format, it makes sense to have them all in a single program (possibly inheriting from a common base scraper).

If not and they are completely unrelated to each other, might as well keep them separate so changes in one have no effect on another.

Update, following edits to question:

Don't change things just for the sake of change. You have something that works, don't mess with it too much.

Since your data sources and data sinks are all separate from each other, combining them into one application will simply create a very complicated application that will be very difficult to change when needed.

Since the scrapers are separate, keep the separation as you have it now.

As sbrenton said, this most falls in with ETL. You should check out Talend Open Studio. It specializes in handling data flows like I imagine yours are as well as other things like duplicate removal, normalization of fields; tens/hundreds of drag and drop ETL components, you can also write custom code as Talend is a code generator as well, either Java or Perl are options. You can also use Talend to execute system commands. I use it for my ETL work, although not in production, in production we will use SSIS, mostly due to lots of other Microsoft products in house.

You may want to use some good scheduling library, like Quartz.NET.

In a few words, here's what you can expect:

    Your tasks are represented by classes and not processes

    You can set and forget tasks and scale across multiple servers

    You have an out-of-the-box system to actually take care of what is needed to be run when, what failed and needs to be re-run, etc. etc.

Source: http://programmers.stackexchange.com/questions/118077/data-scraping-one-application-or-multiple/118098#118098

Roles of Data Mining in Predicting, Tracking, and Containing the Ebola Outbreak

One of the most diverse continents on earth, Africa astounds the world with its vast savannas and great deserts and with its ancient architecture and modern cities, but Africa also has its share of tragedies and woes.

First identified in Democratic Republic of Congo’s Ebola River in 1976, Ebola Hemorrhagic Fever, a deadly zoonotic disease caused by Ebola virus, has been spreading in West Africa like a wildfire, engulfing everything on its way and creating widespread panic.

What has added insult to injury is the fact that the region has long endured the severe consequences of civil wars and social conflicts, and diseases like malaria, HIV/AIDS, yellow fever, cholera etc. have remained endemic to the region for a long time, causing tens of thousands of deaths every year.

Reportedly, Ebola has already killed at least 2,296 people, and there are about 3,685 confirmed cases of infection. Mortality rate has been swinging between 50% to 90%, depending on the quality of care and nutrition. According to WHO, the disease is likely to infect as much as 20,000 people before it is finally brought under control.

Crisis of Data

When it comes to healthcare management, clinical data is one of the key components. The value of data becomes more urgent in the emergency situation like that of West Africa. The more relevant data you have, the bigger picture you can create for taking aggressive measures. To use Peter Drucker’s words, “What gets measured gets managed.”

Factual data is a precondition for the doctors and health science experts working in the field for measuring and managing the situation. Data helps them to assess their successes or failures and reorient their actions. One of the important reasons why the fight against the Ebola outbreak is turning out into a losing battle is the insufficiency of data. Recently, Scientific American magazine wrote:

Right now, there are not even enough beds for sick patients nor enough data coming in to help track cases. Surveillance and tracking of those who were possibly exposed to Ebola remain inadequate.

In Science magazine, Gretchen Vogel suggests that the death toll of Ebola patients could be much higher than it is currently estimated. She says, “Exactly how many unrecorded Ebola deaths have occurred will never be known. Health officials are keeping track of suspected and probable cases, many of which are people who died before they could be tested.” Greg Slabodkin voices similar concerns in Health Data Management and points at the need of an integrated global biosurveillance system.

The absence of reliable and actionable data has badly hampered the efforts of combatting Ebola and providing proper medical care to the victims. CDC Director Dr. Tom Frieden describes it as a “fog-of-war situation”.

Data Mining: Bots Were the First to Warn

When you flip the coin, however, the situation is not completely bleak and desperate. Even if Big Data technologies have fallen short in predicting, tracking, and containing the epidemic, mainly due to the lack of data from the ground, it has not entirely failed. Data scientists and healthcare experts world over are making concerted efforts to know, track, and defeat the Ebola virus—some on the ground and some in their labs.

The increasing level of collaboration among the biomedical specialists, geneticist, virologists, and IT experts has definitely contributed to slow down the transmission of the virulent disease dubbed as “the plague of modern day”. Médecins Sans Frontières and Healthmap.org are the excellent examples in this regard.

    “By deploying bots and crawlers and by using advanced machine learning algorithms, the Boston-based global infectious disease surveillance system, HealthMap was able to predict and raise concerns about the spread of a mysterious hemorrhagic fever in West Africa nine days earlier than WHO did.”

Run by a team of 45 researchers, epidemiologists, and software developers at Boston Children’s Hospital, HealthMap mines data from search engine queries, social media platforms, health information sites, news reports and crowd-sourced information to track the transmission of the disease and provides an up-to-date timeline report with an interactive map, making it easier for the international health agencies to devise more effective action plans.

HealthMap serves as a good example of how crucial Big Data and data mining technologies could be for handling a healthcare emergency with fact-based and data-driven decisions.

Ebola Data

In their letter to The Lancet, research scientist Rashid Ansumana and his colleagues, working on Ebola in Sierra Leone, highlighted on the need of developing epidemic surveillance systems “by adopting new data-sharing technologies.” They wrote, “Emerging technologies can help early warning systems, outbreak response, and communication between health-care providers, wildlife and veterinary professionals, local and national health authorities, and international health agencies.”

Data-Driven Initiatives to Control the Outbreak

The era of systematic use of data for making better epidemiological predictions and for finding effective healthcare solutions began with Google Flue Trends in 2007, and the rapidly developing tools, technologies, and practices in Big Data have increased the roles of data in healthcare management.

There are a number of data-driven undertakings in progress which have contributed to counter the raging spread of Ebola. Brockmann Lab, run by Professor Dirk Brockmann and his colleagues, for example, has created a computer model for studying correlations and probabilities in the explosion of new cases of infection.

World Airtraffic  Transportation and Relative Import Risk, Source: Brockmann Lab

By applying computational and statistical models, they predict which areas, cities or regions in the world are at the risk of becoming the next Ebola epidemic hotspots. Similarly, Alessandro Vespignani–a network scientist, statistical physicist, and Northeastern professor–has been using human mobility network data to track the cases of Ebola infection and dissemination.

The Swedish NGO Flowminder Foundation has been aggregating, mining, and analyzing anonymized mobile phone location data and is developing national mobility estimates for West Africa to help the local and international agencies to combat the disease.

Meanwhile, innovations with Epi Info VHF, a software tool for case management, contact tracing, analysis and reporting services for Ebola and other hemorrhagic fever outbreaks and OpenStreetMap project for getting location information and spatial data of the affected areas have further helped to guide the intervention initiatives.

However, with all optimism about the growing roles of Big Data and data mining, we also need to be mindful about their limitations. Newsweek aptly puts: “While no media-trawling bot could ever replace national and international health agencies, such tools may be starting to help fill in some of the most gaping holes in real-time knowledge.”

Source: http://www.grepsr.com/blog/data-mining-tracking-ebola-outbreak/

Social Media Crawling & Scraping services for Brand Monitoring

Crawling social media sites for extracting information is a fairly new concept – mainly due to the fact that most of the social media networking sites have cropped up in the last decade or so. But it’s equally (if not more) important to grab this ever-expanding User-Generated-Content (UGC) as this is the data that companies are interested in the most – such as product/service reviews, feedback, complaints, brand monitoring, brand analysis, competitor analysis, overall sentiment towards the brand, and so on.

Scraping social networking sites such as Twitter, Linkedin, Google Plus, Instagram etc. is not an easy task for in-house data acquisition departments of most companies as these sites have complex structures and also restrict the amount and frequency of the data that they let out to crawlers. This kind of a task is best left to an expert, such as PromptCloud’s Social Media Data Acquisition Service – which can take care of your end-to-end requirements and provide you with the desired data in a minimal turnaround time. Most of the popular social networking sites such as Twitter and Facebook let crawlers extract data only through their own API (Application Programming Interface), so as to control the amount of information about their users and their activities.

PromptCloud respects all these restrictions with respect to access to content and frequency of hitting their servers to make sure that user information is not compromised and their experience with the site is unhindered.

Social Media Scraping Experts

At PromptCloud, we have developed an expertise in crawling and scraping social media data in real-time. Such data can be from diverse sources such as – Twitter, Linkedin groups, blogs, news, reviews etc. Popular usage of this data is in brand monitoring, trend watching, sentiment/competitor analysis & customer service, among others.

Our low-latency component can extract data on the basis of specific keywords, categories, geographies, or a combination of these. We can also take care of complexities such as multiple languages as well as tweets and profiles of specific users (based on keywords or geographies). Sample XML data can be accessed through this link – demo.promptcloud.com.

Structured data is delivered via a single REST-based API and every time new content is published, the feed gets updated automatically. We also provide data in any other preferred formats (XML, CSV, XLS etc.).

If you have a social media data acquisition problem that you want to get solved, please do get in touch with us.

Source: https://www.promptcloud.com/social-media-networking-sites-crawling-service/

Scraping Twitter Lists To Boost Social Outreach (+ Free Tool!)

I published a post a few weeks ago describing how to build your own twitter custom audience list, outlining a variety of techniques to build up your list.

This post outlines another method (hat tip to Ade Lewis for the idea) which requires you to scrape Twitter directly.

If you want to skip all the explanations and just want to download the Twitter List Scraper tool, here you go…

Download the Twitter Scraper Tool for Windows or Mac (completely free)

Disclaimer: Scraping Twitter is against their Terms of Service, so if you decide to do this you do it at your own risk.

Some Benchmarks

Building custom audiences on Twitter requires you to identify Twitter usernames that might be interested in your service or product.

In my previous posts, one of the methods I employed was to pull a competitor’s link profile and scrape social accounts from the linking domains.

Once you upload a custom list, Twitter goes through a process of ‘matching’ against profiles in their system, to make sure the user exists and hasn’t opted out of tailored ads.

As our data was scraped from a list of unqualified websites, the data matching wasn’t likely to be perfect.

Experiments

Since I published that post, I have been experimenting a fair bit with list building, and have built up around 10 custom audience lists. I‘ve uploaded a total of 48,857 Twitter usernames using this method, but only 29,260 were matched by Twitter (just less than 60% match rate).

From some other experiments where I have had better control over the input data, this match rate was between 70-80%.

Since we’ll be scraping Twitter directly, I expect our match rate to be much higher – 90%+

Finding Relevant Twitter Lists

So, we’re going to scrape Twitter, and the first step is to find Twitter lists that will contain users potentially interested in what we have to offer.

As an example, we’ll pretend we’re marketing a music website, and we’ve produced a survey we want to collect responses for.

An advanced Google query can give us lists of music bloggers: site:twitter.com inurl:lists inurl:members inurl:music “music blogger”

Source: http://urlprofiler.com/blog/scraping-twitter/

Earn Money From Price Comparison Through Web Scraping

Many individuals discover the pot of gold just within their reach. They have realized that there is money in the web. Cyber technology has blessed mankind with so many benefits that makes money very possible by just some clicks on the mouse and keyboard. Building a price comparison website is an effective way of helping clients find their desired products while you as the owner earn money at the same time.

Building price comparison websites

There is indeed much money in building price comparison websites but it is not an easy task especially for a novice in maintaining a website of one’s own. Since this entails some serious programming and ample familiarity with data feeds, you have to have a good working plan. In addition, what you are venturing into is greater than the usual blogs about just anything that you can think of. Furthermore, you are stepping into the vast field of electronic marketing, therefore you must be ready.

The first point of consideration is to identify which products or services are you going to include in your website. Choose a product or service that you and a majority of clients are mostly interested in. Suppose you want you to choose sports as your theme then you can include items and prices of sports gear, clothing such as uniforms, training videos, books, and other safety stuff. You need to do some research and even a survey to determine whether the goods and services you are promoting on your website are in demand and are what most people want to know. Moreover, it is on this stage that you may need the help of experts and veterans in the field of building to be assured that you are on the right track.

In addition, be willing to change in case your chosen category is not gaining readership or visitors. Then evaluate whether you need to expand or to be more specific in your description of the products and the comparison of the prices. Make your site prominent by search engine optimization (SEO) and make sure to acknowledge also that not too many people visit a site that is not free.

Helping visitors choose the best product/services

Good marketing strategy starts with knowing who your target audience are. There is indeed a need to do a lot of planning and research in order to understand your client’s needs and preferences. Moreover, knowing them thoroughly leads to achieving 100% consumer satisfaction. When you have provided everything they need to know about certain products, they would not need to seek elsewhere which will also gain you more regular visitors. Remember that your audience are members of communities and social networks such that there is a great possibility that they would spread the word around about the good services you are offering.

If there is a need to conduct a survey in addition to research, you should resort to it. In this manner you can discover what goods and services are not yet completely exhausted by the other websites or web creators. Ample knowledge about your potential visitors and consumers will surely make you effectively provide them with adequate statistics for their needs.

Your site will then look like a complete guidebook for them that will give them the best value for their money. Therefore, it must be thoroughly filled with product details, uses, options, and prices.

Making money as affiliate of eCommerce websites

Maintaining a price comparison website gives you less worry about getting paid or having your products bought and sold because income comes in through advertising and affiliate sales. Affiliate marketing is a way of earning money online by serving as a publisher for promotion of products, services or sites of businesses. The affiliate receives rewards from businesses for each visitor or client that comes to the business website or buys its product through the efforts of the advertising and promotion that is made by the affiliate. This is the online version of the concept of agent or referral fee sales channel. Aside from website owners, bloggers as well as members of community forums can also serve as affiliates. The affiliate earns money in three ways: through pay per link; pay per sale and pay per lead.

Trust in the reliability of the product - You should have a personal belief or confidence in the product you are promoting not only because it makes you sound more convincing, but also because you need to maintain your clients and establish credibility in your blog or website. In other words, don’t just pick any product. If you cannot use them personally, they should at least have several positive reviews and no negative ones.

Maintain credibility with readers and fellow bloggers - Befriend your readers and your co-bloggers by answering their queries sincerely and quickly. Your friendly attitude can win you their trust which is a very vital element of affiliate marketing.

Do reviews - In addition to publishing price comparison, you can gain more visitors by writing about the product and do proper SEO (Search Engine Optimization). So the expected happens, the more prominent the product becomes online, the higher will be your income.

Link with friends thru social media - Your friends have friends and their friends have also friends. Just think of how powerful your social media site can be when you post your link on your account on Facebook, Twitter or MySpace and others. Since trust is built on friendship, it is easy to get clients from among your friends and their friends.

Overall, you get all pertinent information about certain products through web data mining or web scraping. All you need to do is to be keen to the needs of your clients and use web content extraction efficiently.

Source: http://www.loginworks.com/earn-money-price-comparison-web-scraping/

Social Media Crawling & Scraping services for Brand Monitoring

Crawling social media sites for extracting information is a fairly new concept – mainly due to the fact that most of the social media networking sites have cropped up in the last decade or so. But it’s equally (if not more) important to grab this ever-expanding User-Generated-Content (UGC) as this is the data that companies are interested in the most – such as product/service reviews, feedback, complaints, brand monitoring, brand analysis, competitor analysis, overall sentiment towards the brand, and so on.

Scraping social networking sites such as Twitter, Linkedin, Google Plus, Instagram etc. is not an easy task for in-house data acquisition departments of most companies as these sites have complex structures and also restrict the amount and frequency of the data that they let out to crawlers. This kind of a task is best left to an expert, such as PromptCloud’s Social Media Data Acquisition Service – which can take care of your end-to-end requirements and provide you with the desired data in a minimal turnaround time. Most of the popular social networking sites such as Twitter and Facebook let crawlers extract data only through their own API (Application Programming Interface), so as to control the amount of information about their users and their activities.

PromptCloud respects all these restrictions with respect to access to content and frequency of hitting their servers to make sure that user information is not compromised and their experience with the site is unhindered.

Social Media Scraping Experts

At PromptCloud, we have developed an expertise in crawling and scraping social media data in real-time. Such data can be from diverse sources such as – Twitter, Linkedin groups, blogs, news, reviews etc. Popular usage of this data is in brand monitoring, trend watching, sentiment/competitor analysis & customer service, among others.

Our low-latency component can extract data on the basis of specific keywords, categories, geographies, or a combination of these. We can also take care of complexities such as multiple languages as well as tweets and profiles of specific users (based on keywords or geographies). Sample XML data can be accessed through this link – demo.promptcloud.com.

Structured data is delivered via a single REST-based API and every time new content is published, the feed gets updated automatically. We also provide data in any other preferred formats (XML, CSV, XLS etc.).

If you have a social media data acquisition problem that you want to get solved, please do get in touch with us.

Source: https://www.promptcloud.com/social-media-networking-sites-crawling-service/

What are the ethics of web scraping?

Someone recently asked: "Is web scraping an ethical concept?" I believe that web scraping is absolutely an ethical concept. Web scraping (or screen scraping) is a mechanism to have a computer read a website. There is absolutely no technical difference between an automated computer viewing a website and a human-driven computer viewing a website. Furthermore, if done correctly, scraping can provide many benefits to all involved.

There are a bunch of great uses for web scraping. First, services like Instapaper, which allow saving content for reading on the go, use screen scraping to save a copy of the website to your phone. Second, services like Mint.com, an app which tells you where and how you are spending your money, uses screen scraping to access your bank's website (all with your permission). This is useful because banks do not provide many ways for programmers to access your financial data, even if you want them to. By getting access to your data, programmers can provide really interesting visualizations and insight into your spending habits, which can help you save money.

That said, web scraping can veer into unethical territory. This can take the form of reading websites much quicker than a human could, which can cause difficulty for the servers to handle it. This can cause degraded performance in the website. Malicious hackers use this tactic in what’s known as a "Denial of Service" attack.

Another aspect of unethical web scraping comes in what you do with that data. Some people will scrape the contents of a website and post it as their own, in effect stealing this content. This is a big no-no for the same reasons that taking someone else's book and putting your name on it is a bad idea. Intellectual property, copyright and trademark laws still apply on the internet and your legal recourse is much the same. People engaging in web scraping should make every effort to comply with the stated terms of service for a website. Even when in compliance with those terms, you should take special care in ensuring your activity doesn't affect other users of a website.

One of the downsides to screen scraping is it can be a brittle process. Minor changes to the backing website can often leave a scraper completely broken. Herein lies the mechanism for prevention: making changes to the structure of the code of your website can wreak havoc on a screen scraper's ability to extract information. Periodically making changes that are invisible to the user but affect the content of the code being returned is the most effective mechanism to thwart screen scrapers. That said, this is only a set-back. Authors of screen scrapers can always update them and, as there is no technical difference between a computer-backed browser and a human-backed browser, there's no way to 100% prevent access.

Going forward, I expect screen scraping to increase. One of the main reasons for screen scraping is that the underlying website doesn't have a way for programmers to get access to the data they want. As the number of programmers (and the need for programmers) increases over time, so too will the need for data sources. It is unreasonable to expect every company to dedicate the resources to build a programmer-friendly access point. Screen scraping puts the onus of data extraction on the programmer, not the company with the data, which can work out well for all involved.

Source: https://quickleft.com/blog/is-web-scraping-ethical/

Why Data mining is still a powerful tool to help companies

The ability of Data mining technologies to sift through volumes of data and arrive at predictive information to empower businesses can in no way be undermined. The advent of new techniques and technologies has made the practice more affordable by organizations both big and small. The new technologies have not only helped in reducing the overhead costs of running the data mining exercise, but also simplified the practice making it more accessible for smaller and mid-size companies employ it in their organizational processes. In the current era, information is power and Web Data Mining Technologies are stretching the limits of their capabilities to help organizations acquire that power.

Data Mining Ensures Better Business Decisions

 Organizations usually have access to large databases which store millions of historical data record. Traditional practices of hands-on analysis of patterns and trends of all available data proved to be too cumbersome to be pursued and were soon replaced with shorter and more selective data sets. This caused hidden patterns to remain hidden thus blocking off possibilities for organizations to grow and evolve. However, the advent of Data Mining as a technology that automates the identification of complex patterns in those databases changed all that. Organizations, now, are engaging in a thorough analysis of massive data sets and are moving ahead to extracting meanings and patterns from them. The analysis helps to unlock the hidden patterns and enables organizations to predict future market behavior and be geared with proactive and knowledge driven decisions for the benefit of their business.

Data Mining provides Fraud Detection Capabilities

 Loss in Revenue has definite adverse impacts on a company’s morale. It slackens productivity and slows down their growth. Fraud is one of the common malpractices that eat into the organization’s revenue earning capability. Data Mining helps to prevent this and ensures a steady rise in their revenue graph. Data mining models can be built to predict consumer behavior patterns which help in effectively detecting fraud.

Data Mining Evolves to be Business Focused

 Traditional Data Mining technologies were focused more on algorithms and statistics on delivering results which, though good failed to address the business issues appropriately. The new age data mining technologies, however, have evolved to become business focused. They understand the needs that drive the business and utilize the strong statistical algorithms built into their system to explore, collect, analyze and summarize data that can be made to work for better health of the business.

Data Mining has become more Granular

 As technology evolves, organizations leverage the benefits it generates. Integration of fundamental data mining functionalists into database engines is one such innovation that has helped organizations to thoroughly benefit from its effect. Mining data from within the database instead of Web Data Extraction the data and then analyzing it saves valuable time for the organization. Moreover, as organizations can now drill down into more granular levels of the data therefore there is a higher possibility of ensuring accuracy. Moreover, as data mining software now have a more direct access to the data sets within the database, there is a higher possibility of ensuring a smoother workflow and hence a better performance.

Conclusion

 Data mining, though capable of helping organizations generate good things, however, needs to be used intelligently. It has to be strongly aligned with the organization’s goals and principles in order to ensure appropriate performance that would strengthen the organization adequately.

We are leading Webdatascraping.us company and enough capable to extract website information, review scraping, contact information scraping, business directory scraping, email list scraping etc.

Scraping expert's Amazon Scraper provides huge access to find your desired product on Amazon

Today, with latest advancement of technology we find plenty of ecommerce websites offering huge benefits to people by giving out various products from different categories at an affordable cost. One of the most renowned ecommerce website Amazon has come up with its all new launch of Amazon Scraper for the comfort of their customers. This product Amazon Scraper is also called web harvesting which is a computer software technique for getting out data from websites.

Today anyone can find such web scraping tools that are specifically designed for particular websites. Like for example, Amazon Scraper is also a web scraper tool or technique utilised to crawl, or scrap or even extract the data from the largest e commerce website called Amazon.com. Scrapingexpert.com offers best Amazon scraper for extracting plenty of products from websites easily.

Amazon scraper

Let us see how the Amazon Scraper works:

How to use: Step 1) Select the Category; Enter the (Keyword, UPC, and ASIN) Step 2) Set the delay in seconds Step 3) Click Start

Also you can Scrape the below given details from Amazon.com:

•     Product Title & Description
•     Category & Cost Manufacture,
•     QTY Seller Name,
•     Total Sellers Shipping Cost,
•     Shipping / Product Weight ImageURL, IsBuyBoxFBA, Source Link
•     Stars, Customer Reviews
•     ASIN, UPC, Model Number Sales Rank,
•     Sales Rank In Category
• Here are some interesting Product Features:
•     Single Screen Dashboard that shows total extracted records, extracted keywords, and elapse.
•     Filter Search - Skip data that do not match phrases or keywords
•     Compatible for Microsoft XP/Vista/Windows 7
•     Option to set delay between requests to simulate a human surfing in a browser
•     Extracted data is stored in CSV format, which you can easily open in excel
• Benefits:
•     Less Expensive - With our valuable services, we allow you to save both your efforts and money. We have some competitors who outsource their scraping projects to us.
•     Guaranteed Accurate Results - We assure you get most reliable solutions with accurate results that cannot be collected by any ordinary human being or anyone else.
•     Delivers Fast Results - We promise to get your work done in just few hours, which can take plenty of time if done by someone else. We save your time, workforce and money and give you an opportunity to stand at a distinction over your multiple competitors.
•     System Requirement: Operating System - Windows XP, Windows Vista, Windows 7 Net Framework 2.0

Are you searching for some cost effective programs to extract data of other users? If your answer is yes, then we offer Amazon Screen Scraping which is the best Amazon Screen Scraping method of data extraction. Today, in this competitive world of advanced technology there are multiple companies who claim to offer best Amazon Screen Scraping services, so hiring their services for Amazon Screen Scraping can allow you to scrap almost any data in any format you wish to obtain. Well, we at Scrapingexpert.com study each and every single bit of little details of the scraping project and then provide you with a free quote and the date of completing the work

In order to get accurate data pertaining to a specific product, you can use our Awesome Amazon Scraper Tool. This Awesome Amazon Scraping Tool is very effective tool that will help you to extract information about any product from Amazon.

Websitedatascraping.com is enough capable to web data scraping, website data scraping, web scraping services, website scraping services, data scraping services, product information scraping and yellowpages data scraping.

Life’s Solutions through Web Scraping

Incredibly, there is no other time in human existence that personal data can be accessed as easily and quickly as it is in the present time. Sadly though, records about a person’s activities are kept without even his or her knowledge about them. It is then the act of web scraping that unearths what these are and puts them to commodities of priceless value and of great use.

On the brighter side, solutions about one’s life’s dilemmas can be acquired completely by retrieving the information entered online by every individual. Specifically, it would be more convenient these days to write a person’s biography; evaluate his or her health history; and trace his or her activities through data mining.

Biography

A person’s life story can be known and written about by gleaning through his or her online activities such as emails; purchase records; and every other recorded online presence he or she has made during his or her life time. The biography can be objective as well as subjective: objective in the sense that actual activities and concrete evidences are on record; and subjective in the sense that each activity or data can be analyzed and construed based on other related activities or based on the context where the information is taken or made.

A person’s emails, for instance, can reveal a lot about his or her major decisions and activities in his or her life time. These emails are like journals that directly and indirectly reveal a person’s unique behavior, personality, and preferences. In addition, what he or she exposes through these electronic messages can show the kind of person he or she has been through the different stages in his or her life. It would then be very interesting to discover the many changes in one’s life at specific points and be amazed at how one has matured or developed through the years. Moreover, the person may discover more about himself or herself if he or she would take the time to study his or her own electronic correspondence.

Source:http://www.loginworks.com/blogs/web-scraping-blogs/lifes-solutions-web-scraping/

Data Mining vs Screen-Scraping

Data mining isn't screen-scraping. I know that some people in the room may disagree with that statement, but they're actually two almost completely different concepts.

In a nutshell, you might state it this way: screen-scraping allows you to get information, where data mining allows you to analyze information. That's a pretty big simplification, so I'll elaborate a bit.

The term "screen-scraping" comes from the old mainframe terminal days where people worked on computers with green and black screens containing only text. Screen-scraping was used to extract characters from the screens so that they could be analyzed. Fast-forwarding to the web world of today, screen-scraping now most commonly refers to extracting information from web sites. That is, computer programs can "crawl" or "spider" through web sites, pulling out data. People often do this to build things like comparison shopping engines, archive web pages, or simply download text to a spreadsheet so that it can be filtered and analyzed.

Data mining, on the other hand, is defined by Wikipedia as the "practice of automatically searching large stores of data for patterns." In other words, you already have the data, and you're now analyzing it to learn useful things about it. Data mining often involves lots of complex algorithms based on statistical methods. It has nothing to do with how you got the data in the first place. In data mining you only care about analyzing what's already there.

The difficulty is that people who don't know the term "screen-scraping" will try Googling for anything that resembles it. We include a number of these terms on our web site to help such folks; for example, we created pages entitled Text Data Mining, Automated Data Collection, Web Site Data Extraction, and even Web Site Ripper (I suppose "scraping" is sort of like "ripping"). So it presents a bit of a problem-we don't necessarily want to perpetuate a misconception (i.e., screen-scraping = data mining), but we also have to use terminology that people will actually use.

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Internet Data Mining - How Does it Help Businesses?

Internet has become an indispensable medium for people to conduct different types of businesses and transactions too. This has given rise to the employment of different internet data mining tools and strategies so that they could better their main purpose of existence on the internet platform and also increase their customer base manifold.

Internet data-mining encompasses various processes of collecting and summarizing different data from various websites or webpage contents or make use of different login procedures so that they could identify various patterns. With the help of internet data-mining it becomes extremely easy to spot a potential competitor, pep up the customer support service on the website and make it more customers oriented.

There are different types of internet data_mining techniques which include content, usage and structure mining. Content mining focuses more on the subject matter that is present on a website which includes the video, audio, images and text. Usage mining focuses on a process where the servers report the aspects accessed by users through the server access logs. This data helps in creating an effective and an efficient website structure. Structure mining focuses on the nature of connection of the websites. This is effective in finding out the similarities between various websites.

Also known as web data_mining, with the aid of the tools and the techniques, one can predict the potential growth in a selective market regarding a specific product. Data gathering has never been so easy and one could make use of a variety of tools to gather data and that too in simpler methods. With the help of the data mining tools, screen scraping, web harvesting and web crawling have become very easy and requisite data can be put readily into a usable style and format. Gathering data from anywhere in the web has become as simple as saying 1-2-3. Internet data-mining tools therefore are effective predictors of the future trends that the business might take.

If you are interested to know something more on Web Data Mining and other details, you are welcome to the Screen Scraping Technology site.

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Outsource Data Mining Services to Offshore Data Entry Company

Companies in India offer complete solution services for all type of data mining services.

Data Mining Services and Web research services offered, help businesses get critical information for their analysis and marketing campaigns. As this process requires professionals with good knowledge in internet research or online research, customers can take advantage of outsourcing their Data Mining, Data extraction and Data Collection services to utilize resources at a very competitive price.

In the time of recession every company is very careful about cost. So companies are now trying to find ways to cut down cost and outsourcing is good option for reducing cost. It is essential for each size of business from small size to large size organization. Data entry is most famous work among all outsourcing work. To meet high quality and precise data entry demands most corporate firms prefer to outsource data entry services to offshore countries like India.

In India there are number of companies which offer high quality data entry work at cheapest rate. Outsourcing data mining work is the crucial requirement of all rapidly growing Companies who want to focus on their core areas and want to control their cost.

Why outsource your data entry requirements?

Easy and fast communication: Flexibility in communication method is provided where they will be ready to talk with you at your convenient time, as per demand of work dedicated resource or whole team will be assigned to drive the project.

Quality with high level of Accuracy: Experienced companies handling a variety of data-entry projects develop whole new type of quality process for maintaining best quality at work.

Turn Around Time: Capability to deliver fast turnaround time as per project requirements to meet up your project deadline, dedicated staff(s) can work 24/7 with high level of accuracy.

Affordable Rate: Services provided at affordable rates in the industry. For minimizing cost, customization of each and every aspect of the system is undertaken for efficiently handling work.

Outsourcing Service Providers are outsourcing companies providing business process outsourcing services specializing in data mining services and data entry services. Team of highly skilled and efficient people, with a singular focus on data processing, data mining and data entry outsourcing services catering to data entry projects of a varied nature and type.

Why outsource data mining services?

360 degree Data Processing Operations

Free Pilots Before You Hire

Years of Data Entry and Processing Experience

Domain Expertise in Multiple Industries

Best Outsourcing Prices in Industry

Highly Scalable Business Infrastructure

24X7 Round The Clock Services

The expertise management and teams have delivered millions of processed data and records to customers from USA, Canada, UK and other European Countries and Australia.

Outsourcing companies specialize in data entry operations and guarantee highest quality & on time delivery at the least expensive prices.

Herat Patel, CEO at 3Alpha Dataentry Services possess over 15+ years of experience in providing data related services outsourced to India.

Visit our Facebook Data Entry profile for comments & reviews.

Our services helps to convert any kind of  hard copy sources, our data mining services helps to collect business contacts, customer contact, product specifications etc., from different web sources. We promise to deliver the best quality work and help you excel in your business by focusing on your core business activities. Outsource data mining services to India and take the advantage of outsourcing and save cost.

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Web Data Extraction Services

Web Data Extraction from Dynamic Pages includes some of the services that may be acquired through outsourcing. It is possible to siphon information from proven websites through the use of Data Scrapping software. The information is applicable in many areas in business. It is possible to get such solutions as data collection, screen scrapping, email extractor and Web Data Mining services among others from companies providing websites such as Scrappingexpert.com.

Data mining is common as far as outsourcing business is concerned. Many companies are outsource data mining services and companies dealing with these services can earn a lot of money, especially in the growing business regarding outsourcing and general internet business. With web data extraction, you will pull data in a structured organized format. The source of the information will even be from an unstructured or semi-structured source.

In addition, it is possible to pull data which has originally been presented in a variety of formats including PDF, HTML, and test among others. The web data extraction service therefore, provides a diversity regarding the source of information. Large scale organizations have used data extraction services where they get large amounts of data on a daily basis. It is possible for you to get high accuracy of information in an efficient manner and it is also affordable.

Web data extraction services are important when it comes to collection of data and web-based information on the internet. Data collection services are very important as far as consumer research is concerned. Research is turning out to be a very vital thing among companies today. There is need for companies to adopt various strategies that will lead to fast means of data extraction, efficient extraction of data, as well as use of organized formats and flexibility.

In addition, people will prefer software that provides flexibility as far as application is concerned. In addition, there is software that can be customized according to the needs of customers, and these will play an important role in fulfilling diverse customer needs. Companies selling the particular software therefore, need to provide such features that provide excellent customer experience.

It is possible for companies to extract emails and other communications from certain sources as far as they are valid email messages. This will be done without incurring any duplicates. You will extract emails and messages from a variety of formats for the web pages, including HTML files, text files and other formats. It is possible to carry these services in a fast reliable and in an optimal output and hence, the software providing such capability is in high demand. It can help businesses and companies quickly search contacts for the people to be sent email messages.

It is also possible to use software to sort large amount of data and extract information, in an activity termed as data mining. This way, the company will realize reduced costs and saving of time and increasing return on investment. In this practice, the company will carry out Meta data extraction, scanning data, and others as well.

please visit Data extraction services to take care of your online as well as offline projects and to get your work done in given time frame with exceptional quality.

Source: http://ezinearticles.com/?Web-Data-Extraction-Services&id=4733722

Know the Different Types of Mining Processes

Mining has become a controversial industry because of its "devastating" effect to the environment and the ecosystem. However, it has contributed so much to civilization that without it, we could never be where we are today in many aspects.

There are two basic methods of mining. These are the surface and the underground mining processes:

1. Surface Mining

This involves the mining of minerals located at or near the surface of the earth. This encompasses at least six processes and these are:

• Strip Mining - this involves the stripping of the earth's surface by heavy machinery. This method is generally targeted at extracting coal or sedimentary rocks that lay near the earth's surface.

• Placer Mining - this involves the extraction of sediments in sand or gravel. It is a simple, old-fashioned way of mining. This method is generally applicable to gold and precious gems that are carried by the flow of water.

• Mountain Top Mining - this is a new method which involves blasting of a mountain top to expose coal deposits that lie underneath the mountain crest.

• Hydraulic Mining - this is an obsolete method that involves jetting the side of a mountain or hill with high pressure water to expose gold and other precious metals.

• Dredging - it involves the removal of rocks, sand and silt underneath a body of water to expose the minerals.

• Open Pit - this is the most common mining method. It involves the removal of the top layers of soil in search for gold or buried treasure. The miner digs deeper and deeper until a large, open-pit is created.

2. Underground Mining

This is the process in which a tunnel is made into the earth to find the mineral ore. The mining operation is usually performed with the use of underground mining equipment. Underground mining is done through the following methods:

• Slope Mining - it involves the creation of slopes into the ground in order to reach the ore or mineral deposit. This process is generally applied in coal mining.

• Hard rock - this method uses dynamite or giant drills to create large, deep tunnels. The miners support the tunnels with pillars to prevent them from collapsing. This is a large-scale mining process and is usually applied in the extraction of large copper, tin, lead, gold or silver deposits.

• Drift mining - this method is applicable only when the target mineral is accessible from the side of a mountain. It involves the creation of a tunnel that's slightly lower than the target mineral. The gravity makes the deposit fall to the tunnel where miners can collect them.

• Shaft method - this involves the creation of a vertical passageway that goes deep down underground where the deposit is located. Because of the depth, miners are brought in and out of the pit with elevators.

• Borehole method - this involves the use of a large drill and high pressure water to eject the target mineral.

These are the basic methods used in the extraction of common minerals. There are more complex systems, but still, they are based on these fundamental processes.

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New Technique to Boost US Uranium Mining - Satellite Plants

If you study the news releases, several companies have discussed the setting up of one or more satellite plants in conjunction with their In Situ Recovery (ISR) uranium mining operations. In order to help readers better understand what exactly a 'satellite plant' is, we interviewed Mark Pelizza of Uranium Resources about how this relatively new operational technique is presently being used at the company's Texas operations. This is part two our six-part series, describing the evolution of ISR uranium mining, building upon last year's basic series on this subject.

A larger uranium deposit, such as one at Cameco's Smith Ranch in Wyoming, requires a Central Processing Plant. The 'mother plant,' as it is called in the trade, can complete the entire processing cycle from uranium extraction through loading the resin, stripping the uranium from the resin with a solvent (elution), precipitating, drying and packaging.

With a satellite plant, also known as a Remote Ion Exchange (RIX), smaller and distant deposits can also be mined and then trucked to the mother plant. With an RIX operation, the front-end of the 'milling' cycle can be begun independent of the much larger mother plant. It is the same ion exchange column found at central processing facility. The mobility factor makes RIX an attractive proposition for many of the new-breed uranium producers. Rather than piping the water and uranium across a longer distance to the mother plant for the entire processing cycle, the modular nature of RIX allows for multiple columns at each well field doing the ion exchange on the spot.

This is not a new idea, but one which has instead been re-designed by Uranium Resources and is also used elsewhere. In the early 1970s, Conoco and Pioneer Nuclear Corporation formed the Conquista project in south Texas. Uranium was open-pit mined at between ten and fifteen mines within a thirty-five mile radius and in two counties. Trucks hauled ore to the 1750-ton/day processing mill near Falls City in Karnes County.

"The trademark of south Texas is a lot of small million-pound-style deposits," Mark Pelizza told us. "I think we are heading in the right direction to exploit those small deposits." Trucking resin beads loaded with uranium is different from trucking ore which has been conventionally mined. Small, scattered uranium deposits aren't only found in Texas. There are numerous smaller ISR-amenable properties in Wyoming, New Mexico, Colorado and South Dakota.

"About half the uranium deposits in New Mexico can be mined with ISR," Pelizza said, "and the other half would require conventional mining." A number of companies we've interviewed have geographically diverse, but relatively nearby properties within their portfolio. Several companies with whom we discussed RIX have already made plans to incorporate this method into their mining operations.

The sole-use semi-trailer trucks hauling the yellowcake slurry are different from the typical dump trucks used in conventional mining. According to Pelizza, the truck carries a modified bulk cement trailer with three compartments. The three compartments, or cells, each have a function. One cell holds the uranium-loaded resin, one cell is empty and the third has unloaded resin.

As per Department of Transportation (DOT) regulations, no liquids are permitted during the transportation process. Each container run between the wellfield and the mother plant can bring between 2,000 and 3,000 pounds of uranium-in-resin, depending upon how large the container is designed. The 'loaded' cell holds between 300 and 500 pounds of resin with six to eight pounds of uranium per cubic foot of resin. Age of the resin is important, too. New resin can hold up to ten pounds of uranium per cubic foot and can decline to five pounds of uranium per cubic foot after several years.

As we found with a conventional Ion Exchange process, the RIX system is run as a closed loop pressurized process to prevent the release of radon gas into the atmosphere. The uranium is oxidized, mobilized and pumped out of the sandstone formation into a loaded pipeline and ends up in an ion exchange column at the mining site. Inside the columns, uranium is extracted through an ion exchange process - a chloride ion on a resin bead exchanges for a uranium ion. After the fluid has been stripped of uranium, it is sent back to the wellfield as barren solution, minus the bleed.

When the ion exchange column is fully loaded, the column is taken offline. The loaded resin is transferred from the column to a bulk cement trailer, which is a pressurized vessel comprised of carbon steel with a rubberized internal lining. The resin trailer is connected to the ion exchange column transfer piping with hoses. After it has been drained of any free water, the uranium-loaded resin can be transported as a solid, known as 'wet yellowcake' to the mother plant. There, the yellowcake slurry is stripped from the resin, precipitated and vacuum-dried with a commercial-grade food dryer.

Capital costs can be dramatically reduced with the satellite plants, or RIX units. "Well field installation can cost more than RIX," Pelizza noted. Often, installing a well field can start at approximately $10 million and run multiples higher, depending upon the spacing of the wells and the depth at which uranium is mined. Still, compared to conventional mining, the entire ISR well field mining and solvent circuit method of uranium processing is relatively inexpensive.

We checked with a number of near-term producers - those with uranium projects in Wyoming - and discovered at least three companies planned to utilize one or more satellite plants, or RIX, in their operations. A company's reason for utilizing this method is to minimize capital and operating expenses while mining multiple smaller deposits within the same area. Water is treated at the RIX to extract the uranium instead of piping it across greater distances to a full-sized plant. Pelizza said, "The potential for pipeline failure and spillage from a high-flow trunk line is eliminated."

Strathmore Minerals vice president of technical services John DeJoia said his company was moving forward with a new type of Remote Ion Exchange design, but would not provide details. UR-Energy chief executive Bill Boberg said his company would use an RIX for either Lost Soldier or Lost Creek in Wyoming, perhaps for both. Uranerz Energy chief executive Glenn Catchpole told us he planned to probably set up two RIX operations at the company's Wyoming properties and build a central processing facility.

"We are working on a standardized design of the remote ion exchange unit so it doesn't require any major licensing action," Pelizza said. "If you can speed up the licensing time, perhaps it would take one to two years rather than three to five years."

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