How Data Mining is Useful to Companies?

How Data Mining is Useful to Companies?

Every business, organization and government bodies are collecting large amount of data for research and development. Such huge database can make them to have the information on hand when required. But most important is that it takes much time to find important information from the data. "If you want to grow rapidly, you must take quick and accurate decisions to grab timely available opportunities."

By applying the process of data mining, you can easily extract and filter required information from data. It is a processing of refining data and extracting important information. This process is mainly divided into 3 sections; pre-processing, mining and validation. In pre-processing, large amount of relevant data are collected. The mining section includes data classification, clustering, error correction and linking information. The last but important is validate without which you can not make trust on information. In short, data mining is a process of converting data into authentic information.

Let's have look on how data mining is useful to companies.

Fast and Feasible Decisions: To search information from huge bundle of data require more time. It also irritates a person who is doing such. With annoyed mind one can not take accurate decisions that's for sure. By having help of data mining, one can easily get information and make fast decisions. It also helps to compare information with various factors so the decisions become more reliable. Data mining is helpful in every decision to make it quick and feasible.

Powerful Strategies: After data mining, information becomes precise and easy to understand. While making strategies, one can easily analyze information in various dimensions. This analysis helps to get real idea about the strategy implementation. Management bodies can implement powerful strategies effectively to expand business boundaries.

Competitive Advantage: Information is easily available and precise so that one can compare it with competitors' information. It is very much required that you must compare the data otherwise you will have to suffer in business. After doing competitive analysis, one can make corrective decisions to go ahead from competitors. This way company can gain competitive advantage.

Your business can get all the benefits of data mining at cutting rates through outsourcing.

Source : http://ezinearticles.com/?How-Data-Mining-is-Useful-to-Companies?&id=2835042

Data Scrapping

Data Scrapping

People who are involved in business activities might have came across a term Data Scrapping. It is a process in which data or information can be extracted from the Portable Document Format file. They are easy to use tools that can automatically arrange the data that are found in different format in the internet. These advanced tools can collect useful information's according to the need of the user. What the user needs to do is simply enter the key words or phrases and the tool will extract all the related information available from the Portable Document Format file. It is widely used to take information's from the no editable format.

The main advantage of Portable Document Format files are they protect the originality of the document when you convert the data from Word to PDF. The size of the file is reduced by compression algorithems when the file are heavier due to the graphics or the images in the content. A Portable Document Format is independent of any software or hardware for installation. It allows encryption of files which enhances the security of your contents.

Although the Portable Document Format files have many advantages,it too have many other challenges. For example, you want to access a data that you found on the internet and the author encrypted the file preventing you from printing the file, you can easily do the scrapping process. These functions are easily available on the internet and the user can choose according to their needs. Using these programs you can extract the data that u need.

Source : http://ezinearticles.com/?Data-Scrapping&id=4951020

Web Data Extraction Services

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.

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

Scraping in PDF Files - Improving Accessibility

Scraping in PDF Files - Improving Accessibility

Scraping of data is one procedure where mechanically information is sorted out that is contained on the Net in HTML, PDF and various other documents. It is also about collecting relevant data and saving it in spreadsheets or databases for retrieval purposes. On a majority of sites, text content can be easily accessed in the source code however a good number of business houses are making use of Portable Document Format. This format had been launched by Adobe and documents in this format can be easily viewed on almost any operating system. Some people convert documents from word to PDF when they need sending files over the Net and many convert PDF to word so that they could edit their documents. The best benefit that one gets for making use of it is that documents look a replica of the original and there is no form of disturbance in viewing them as they appear organized and same on almost all operating systems. The downside of the format is that text in such files is converted into a picture or image and then copying and pasting it is not possible any more.

Scraping in this format is a procedure where data is scraped that is available in such files. Most diverse of the tools is needed in order to carry out scraping in a document that is created in this format. You'd find two main forms of PDF files where one is built from a text file and the other firm is where it is built from some image. There is software brought by Adobe itself which can capably do scraping in text based files. For files that are image-based, there is a need to make use of special application for the task.

OCR program is one primary tool to be used for such a matter. Optical Recognition Program is capable in scanning documents for small picture that can be segregated into letters. The pictures are compared with actual letters and given they match well; the letters get copied into one file. These programs are able to do scraping in an apt way in image-based files pretty much aptly however it cannot be said that they are perfect. Once the procedure is done you could search through data so as to find those areas and parts which you had been looking for. More often than not it is difficult to find a utility that can obtain exact data that is needed without proper customization. But if thoroughly checked, you cou

Source: http://ezinearticles.com/?Scraping-in-PDF-Files---Improving-Accessibility&id=6108439

Web Data Extraction Services and Data Collection Form Website Pages

Web Data Extraction Services and Data Collection Form Website Pages

For any business market research and surveys plays crucial role in strategic decision making. Web scrapping and data extraction techniques help you find relevant information and data for your business or personal use. Most of the time professionals manually copy-paste data from web pages or download a whole website resulting in waste of time and efforts.

Instead, consider using web scraping techniques that crawls through thousands of website pages to extract specific information and simultaneously save this information into a database, CSV file, XML file or any other custom format for future reference.

Examples of web data extraction process include:
• Spider a government portal, extracting names of citizens for a survey
• Crawl competitor websites for product pricing and feature data
• Use web scraping to download images from a stock photography site for website design

Automated Data Collection
Web scraping also allows you to monitor website data changes over stipulated period and collect these data on a scheduled basis automatically. Automated data collection helps you discover market trends, determine user behavior and predict how data will change in near future.

Examples of automated data collection include:
• Monitor price information for select stocks on hourly basis
• Collect mortgage rates from various financial firms on daily basis
• Check whether reports on constant basis as and when required

Using web data extraction services you can mine any data related to your business objective, download them into a spreadsheet so that they can be analyzed and compared with ease.

In this way you get accurate and quicker results saving hundreds of man-hours and money!

With web data extraction services you can easily fetch product pricing information, sales leads, mailing database, competitors data, profile data and many more on a consistent basis.

Source:http://ezinearticles.com/?Web-Data-Extraction-Services-and-Data-Collection-Form-Website-Pages&id=4860417

How Xpath Plays Vital Role In Web Scraping

How Xpath Plays Vital Role In Web Scraping

XPath is a language for finding information in structured documents like XML or HTML. You can say that XPath is (sort of) SQL for XML or HTML files. XPath is used to navigate through elements and attributes in an XML or HTML document.

To understand XPath we must be clear about elements and nodes which are the building blocks of XML and HTML. Let’s talk about them. Here is an example element in an HTML document:

   <a class=”hyperlink” href=http://www.google.com>google</a>

Copy the above text to a file, name it as sample.html and open it in a browser. This will end up as a text link displaying the words “google” and it will take you to www.google.com. For each element there are three main parts: The type, the attributes, andthe text. They are listed below:

 a                                 Type
class,  href                Attributes
google                       Text

Let’s grab some XPath developer tools. I am on Firebug for Firefox or you can use Chrome’s developer tools. We will now form some XPath expressions to extract data from the above element. We will also verify the XPath by using Firebug Console.

For extracting the text “google”:

   //a[@href]/text()   

   //a[@class=”hyperlink”]/text()
 
For extracting the hyperlink i.e. ”www.google.com” :

   //a/@href
//a[@class=”hyperlink”]/@href

That’s all with a single element but in reality, you need to deal with more complex forms.

Let’s proceed to the idea of nodes, and its familial relationship of HTML elements. Look at this example code:

 <div title=”Section1″>

   <table id=”Search”>

       <tr class=”Yahoo”>Yahoo Search</tr>

       <tr class=”Google”>Google Search</tr>

   </table>

</div>

 Notice the </div> at the bottom? That means the table and tr elements are contained within the div. These other elements are considered descendants of the div. The table is a child, and the tr is a grandchild (and so on and so forth). The two tr elements are considered siblings each other. This is vital, as XPath uses these relationships to find your element.

So suppose you want to find the Google item. Any of the following expressions will work:

   //tr[@class=’Google’]
   //div/table/tr[2]
  //div[@title=”Section1″]//tr

So let’s analyze the expressions. We start at the top element (also known as a node). The // means to search all descendants, / means to just look at the current element’s children. So //div means look through all descendants for a div element. The brackets [] specify something about that element. So we can look for an attribute with the @ symbol, or look for text with the text() function. We can chain as many of these together as we can.

Here is a quick reference:

   //             Search all descendant elements
   /              Search all child elements
   []             The predicate (specifies something about the element you are looking for)
   @           Specifies an element attribute. (For example, @title)
   
   .               Specifies the current node (useful when you want to look for an element’s children in the predicate)
   ..              Specifies the parent node
  text()       Gets the text of the element.
   
In the context of web scraping, XPath is a nice tool to have in your belt, as it allows you to write specifications of document locations more flexibly than CSS selectors.

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Source: http://blog.datahut.co/how-xpath-plays-vital-role-in-web-scraping/

Why Outsourcing Data Mining Services?

Why Outsourcing Data Mining Services?

Are huge volumes of raw data waiting to be converted into information that you can use? Your organization's hunt for valuable information ends with valuable data mining, which can help to bring more accuracy and clarity in decision making process.

Nowadays world is information hungry and with Internet offering flexible communication, there is remarkable flow of data. It is significant to make the data available in a readily workable format where it can be of great help to your business. Then filtered data is of considerable use to the organization and efficient this services to increase profits, smooth work flow and ameliorating overall risks.

Data mining is a process that engages sorting through vast amounts of data and seeking out the pertinent information. Most of the instance data mining is conducted by professional, business organizations and financial analysts, although there are many growing fields that are finding the benefits of using in their business.

Data mining is helpful in every decision to make it quick and feasible. The information obtained by it is used for several applications for decision-making relating to direct marketing, e-commerce, customer relationship management, healthcare, scientific tests, telecommunications, financial services and utilities.

Data mining services include:

•     Congregation data from websites into excel database
•     Searching & collecting contact information from websites
•     Using software to extract data from websites
•     Extracting and summarizing stories from news sources
•     Gathering information about competitors business

In this globalization era, handling your important data is becoming a headache for many business verticals. Then outsourcing is profitable option for your business. Since all projects are customized to suit the exact needs of the customer, huge savings in terms of time, money and infrastructure can be realized.

Advantages of Outsourcing Data Mining Services:

•     Skilled and qualified technical staff who are proficient in English
•     Improved technology scalability
•     Advanced infrastructure resources
•     Quick turnaround time
•     Cost-effective prices
•     Secure Network systems to ensure data safety
•     Increased market coverage

Outsourcing will help you to focus on your core business operations and thus improve overall productivity. So data mining outsourcing is become wise choice for business. Outsourcing of this services helps businesses to manage their data effectively, which in turn enable them to achieve higher profits.

Source: http://ezinearticles.com/?Why-Outsourcing-Data-Mining-Services?&id=3066061

What are the ethics of web scraping?

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/

Benefits of Ruby over Python & R for Web Scraping

Benefits of Ruby over Python & R for Web Scraping

In this data driven world, you need to be constantly vigilant, as information and key data for an organization keeps changing all the while. If you get the right data at the right time in an efficient manner, you can stay ahead of competition. Hence, web scraping is an essential way of getting the right data. This data is crucial for many organizations, and scraping technique will help them keep an eye on the data and get the information that will benefit them further.

Web scraping involves both crawling the web for data and extracting the data from the page. There are several languages which programmers prefer for web scraping, the top ones are Ruby, Python & R. Each language has its own pros and cons over the other, but if you want the best results and a smooth flow, Ruby is what you should be looking for.

Ruby is very good at production deployments and using Ruby, Redis & Chef have proven to be a great combination. String manipulation in Ruby is very easy because it is based on Perl syntax. Also, Ruby is great for analyzing web pages using  one of the very powerful gems called Nokogiri. Nokogiri is much easier to use as compared to other packages and libraries used by R and Python respectively. Nokogiri can deal with broken HTML / HTML fragments easily. Ruby also has many extensions, such as Sanitize and Loofah, that can help clean up broken HTML.

Python programmers widely use a library called Beautiful Soup for pulling data out of HTML & XML files. It works with your favorite parser to provide idiomatic ways of navigating, searching, and modifying the parse tree. It commonly saves programmers hours or days of work. R programmers have a new package called rvest that makes it easy to scrape data from html web pages, by libraries like beautiful soup. It is designed to work with magrittr so that you can express complex operations as elegant pipelines composed of simple, easily understood pieces.

To help you understand it more effectively, below is a comprehensive infographic for the same.

Ruby is far ahead of Python & R for cloud development and deployments.  The Ruby Bundler system is just great for managing and deploying packages from Github. Using Chef, you can start up and tear down nodes on EC2, at will, and monitor for failures,  scale up or down, reset your IP addresses, etc. Ruby also has great testing frameworks like Fakeweb and Capybara, making it almost trivial to build a great suite of unit tests and to include advanced features, like crawling  and scraping using webkit / selenium. 

The only disadvantage to Ruby is lack of machine learning and NLP toolkits, making it much harder to emulate the capacity of a tool like Pattern.  It can still be done, however, since most of the heavy lifting can be done asynchronously using Unix tools like liblinear or vowpal wabbit.

Conclusion

Each language has its plus point and you can pick the one which you are most comfortable with. But if you are looking for smooth web scraping experience, then Ruby is the best option. That has been our choice too for years at PromptCloud for the best web scraping results. If you have any further questions about this, then feel free to get in touch with us.

Source: https://www.promptcloud.com/blog/benefits-of-ruby-for-web-scraping

How to use Social Media Scraping to be your Competitors’ Nightmare

How to use Social Media Scraping to be your Competitors’ Nightmare

Big data and competitive intelligence have been in the limelight for quite some time now. The almost magical power of big data to help a company make just the right decisions have been talked about a lot. When it comes to big data, the kind of benefits that a business can get totally depends upon the sources they acquire it from. Social media is one of the best sources from where you can get data that helps your business in a multitude of ways. Now that every business is deep rooted on the internet, social media data becomes all the more relevant and crucial. Here is how you can use data scraped from social media sites to get an edge in the competition.

Keeping watch on your competitors

Social media is the best place to watch your competitors’ activity and take counter initiatives to keep up or take over them. If you want to know what your competitors are up to, a social media scraping setup for scraping the posts that mention your competitors’ brand/product names can do the trick. This can also be used to learn a thing or two from their activities on social media so that you can take respective measures to stay ahead of them. For example, you could know if your competitor is running a special promotional offer at the moment and come up with something better than theirs to keep up. This can do wonders if you are in a highly competitive industry like Ecommerce where the competition is intense. If you are not using some help from web scraping technology to keep a close watch on your competitors, you could easily get left over in this fast-paced business scene.

Solving customer issues at the earliest

Customers are vocal about their experience with different products and services on social media sites these days. If you have a customer whose issue was left unsolved, there is a good chance that he/she will take it to the social media to vent the frustration. Watching out for such instances and giving them prompt support should be something you should do if you want to retain these customers and stop them from ruining your brand’s image. By scraping social media sites for posts that mention your product/service, you can easily find out if there are such grievances from customers. This can make sure to an extent that you don’t let unhappy customers stay that way, which eventually hurts your business in the long run. Customers can make or break your company, so using social media scraping to serve the customers better can help you succeed eventually.

Sentiment analysis

Social media data can play a good job at helping you understand user sentiments. With the help of social media scraping, a business can get the big picture about general perception of their brand by their users. This can go a long way since this level of feedback can help you fix unnoticed issues with your company and service quickly. By rectifying them, you can make your brand more appealing to the customers. Sentiment analysis will provide you with the opportunity to transform your business into how customers want it to be. Social media scraping is the one and only way to have access to this user sentiment data which can help you optimize your business for the customers.

Web crawling for social media data

When social media data possess so much value to businesses, it makes sense to look for efficient ways to gather and use this data. Manually scrolling through millions of tweets doesn’t make sense, this is why you should use social media scraping to aggregate the relevant data for your business. Besides, web scraping technologies make it possible to handle huge amounts of data with ease. Since the size of data is huge when it comes to business related requirements, web scraping is the only scalable solution worth considering. To make things even simpler, there are reliable web scraping solutions that offer social media scraping services for brand monitoring.

Bottom line

Since social media has become an integral part of online businesses, the data available on these sites possess immense value to companies in every industry. Social media scraping can be used for brand monitoring and gaining competitive intelligence that can be used to optimize your business model for maximum effectiveness. This will in turn make your company stand out from the competition and the added advantage of insights gained from social media data will help you to take over your competitors.

Source: https://www.promptcloud.com/blog/social-media-scraping-for-competitive-intelligence

Three Common Methods For Web Data Extraction

Three Common Methods For Web Data Extraction

Probably the most common technique used traditionally to extract data from web pages this is to cook up some regular expressions that match the pieces you want (e.g., URL's and link titles). Our screen-scraper software actually started out as an application written in Perl for this very reason. In addition to regular expressions, you might also use some code written in something like Java or Active Server Pages to parse out larger chunks of text. Using raw regular expressions to pull out the data can be a little intimidating to the uninitiated, and can get a bit messy when a script contains a lot of them. At the same time, if you're already familiar with regular expressions, and your scraping project is relatively small, they can be a great solution.

Other techniques for getting the data out can get very sophisticated as algorithms that make use of artificial intelligence and such are applied to the page. Some programs will actually analyze the semantic content of an HTML page, then intelligently pull out the pieces that are of interest. Still other approaches deal with developing "ontologies", or hierarchical vocabularies intended to represent the content domain.

There are a number of companies (including our own) that offer commercial applications specifically intended to do screen-scraping. The applications vary quite a bit, but for medium to large-sized projects they're often a good solution. Each one will have its own learning curve, so you should plan on taking time to learn the ins and outs of a new application. Especially if you plan on doing a fair amount of screen-scraping it's probably a good idea to at least shop around for a screen-scraping application, as it will likely save you time and money in the long run.

So what's the best approach to data extraction? It really depends on what your needs are, and what resources you have at your disposal. Here are some of the pros and cons of the various approaches, as well as suggestions on when you might use each one:

Raw regular expressions and code

Advantages:

- If you're already familiar with regular expressions and at least one programming language, this can be a quick solution.

- Regular expressions allow for a fair amount of "fuzziness" in the matching such that minor changes to the content won't break them.

- You likely don't need to learn any new languages or tools (again, assuming you're already familiar with regular expressions and a programming language).

- Regular expressions are supported in almost all modern programming languages. Heck, even VBScript has a regular expression engine. It's also nice because the various regular expression implementations don't vary too significantly in their syntax.

Disadvantages:

- They can be complex for those that don't have a lot of experience with them. Learning regular expressions isn't like going from Perl to Java. It's more like going from Perl to XSLT, where you have to wrap your mind around a completely different way of viewing the problem.

- They're often confusing to analyze. Take a look through some of the regular expressions people have created to match something as simple as an email address and you'll see what I mean.

- If the content you're trying to match changes (e.g., they change the web page by adding a new "font" tag) you'll likely need to update your regular expressions to account for the change.

- The data discovery portion of the process (traversing various web pages to get to the page containing the data you want) will still need to be handled, and can get fairly complex if you need to deal with cookies and such.

When to use this approach: You'll most likely use straight regular expressions in screen-scraping when you have a small job you want to get done quickly. Especially if you already know regular expressions, there's no sense in getting into other tools if all you need to do is pull some news headlines off of a site.

Ontologies and artificial intelligence

Advantages:

- You create it once and it can more or less extract the data from any page within the content domain you're targeting.

- The data model is generally built in. For example, if you're extracting data about cars from web sites the extraction engine already knows what the make, model, and price are, so it can easily map them to existing data structures (e.g., insert the data into the correct locations in your database).

- There is relatively little long-term maintenance required. As web sites change you likely will need to do very little to your extraction engine in order to account for the changes.

Disadvantages:

- It's relatively complex to create and work with such an engine. The level of expertise required to even understand an extraction engine that uses artificial intelligence and ontologies is much higher than what is required to deal with regular expressions.

- These types of engines are expensive to build. There are commercial offerings that will give you the basis for doing this type of data extraction, but you still need to configure them to work with the specific content domain you're targeting.

- You still have to deal with the data discovery portion of the process, which may not fit as well with this approach (meaning you may have to create an entirely separate engine to handle data discovery). Data discovery is the process of crawling web sites such that you arrive at the pages where you want to extract data.

When to use this approach: Typically you'll only get into ontologies and artificial intelligence when you're planning on extracting information from a very large number of sources. It also makes sense to do this when the data you're trying to extract is in a very unstructured format (e.g., newspaper classified ads). In cases where the data is very structured (meaning there are clear labels identifying the various data fields), it may make more sense to go with regular expressions or a screen-scraping application.

Screen-scraping software

Advantages:

- Abstracts most of the complicated stuff away. You can do some pretty sophisticated things in most screen-scraping applications without knowing anything about regular expressions, HTTP, or cookies.

- Dramatically reduces the amount of time required to set up a site to be scraped. Once you learn a particular screen-scraping application the amount of time it requires to scrape sites vs. other methods is significantly lowered.

- Support from a commercial company. If you run into trouble while using a commercial screen-scraping application, chances are there are support forums and help lines where you can get assistance.

Disadvantages:

- The learning curve. Each screen-scraping application has its own way of going about things. This may imply learning a new scripting language in addition to familiarizing yourself with how the core application works.

- A potential cost. Most ready-to-go screen-scraping applications are commercial, so you'll likely be paying in dollars as well as time for this solution.

- A proprietary approach. Any time you use a proprietary application to solve a computing problem (and proprietary is obviously a matter of degree) you're locking yourself into using that approach. This may or may not be a big deal, but you should at least consider how well the application you're using will integrate with other software applications you currently have. For example, once the screen-scraping application has extracted the data how easy is it for you to get to that data from your own code?

When to use this approach: Screen-scraping applications vary widely in their ease-of-use, price, and suitability to tackle a broad range of scenarios. Chances are, though, that if you don't mind paying a bit, you can save yourself a significant amount of time by using one. If you're doing a quick scrape of a single page you can use just about any language with regular expressions. If you want to extract data from hundreds of web sites that are all formatted differently you're probably better off investing in a complex system that uses ontologies and/or artificial intelligence. For just about everything else, though, you may want to consider investing in an application specifically designed for screen-scraping.

As an aside, I thought I should also mention a recent project we've been involved with that has actually required a hybrid approach of two of the aforementioned methods. We're currently working on a project that deals with extracting newspaper classified ads. The data in classifieds is about as unstructured as you can get. For example, in a real estate ad the term "number of bedrooms" can be written about 25 different ways. The data extraction portion of the process is one that lends itself well to an ontologies-based approach, which is what we've done. However, we still had to handle the data discovery portion. We decided to use screen-scraper for that, and it's handling it just great. The basic process is that screen-scraper traverses the various pages of the site, pulling out raw chunks of data that constitute the classified ads. These ads then get passed to code we've written that uses ontologies in order to extract out the individual pieces we're after. Once the data has been extracted we then insert it into a database.

Source: http://ezinearticles.com/?Three-Common-Methods-For-Web-Data-Extraction&id=165416

Difference between Data Mining and KDD

Difference between Data Mining and KDD

Data, in its raw form, is just a collection of things, where little information might be derived. Together with the development of information discovery methods(Data Mining and KDD), the value of the info is significantly improved.

Data mining is one among the steps of Knowledge Discovery in Databases(KDD) as can be shown by the image below.KDD is a multi-step process that encourages the conversion of data to useful information. Data mining is the pattern extraction phase of KDD. Data mining can take on several types, the option influenced by the desired outcomes.

Knowledge Discovery in Databases Steps
Data Selection

KDD isn’t prepared without human interaction. The choice of subset and the data set requires knowledge of the domain from which the data is to be taken. Removing non-related information elements from the dataset reduces the search space during the data mining phase of KDD. The sample size and structure are established during this point, if the dataset can be assessed employing a testing of the info.
Pre-processing

Databases do contain incorrect or missing data. During the pre-processing phase, the information is cleaned. This warrants the removal of “outliers”, if appropriate; choosing approaches for handling missing data fields; accounting for time sequence information, and applicable normalization of data.
Transformation

Within the transformation phase attempts to reduce the variety of data elements can be assessed while preserving the quality of the info. During this stage, information is organized, changed in one type to some other (i.e. changing nominal to numeric) and new or “derived” attributes are defined.
Data mining

Now the info is subjected to one or several data-mining methods such as regression, group, or clustering. The information mining part of KDD usually requires repeated iterative application of particular data mining methods. Different data-mining techniques or models can be used depending on the expected outcome.
Evaluation

The final step is documentation and interpretation of the outcomes from the previous steps. Steps during this period might consist of returning to a previous step up the KDD approach to help refine the acquired knowledge, or converting the knowledge in to a form clear for the user.In this stage the extracted data patterns are visualized for further reviews.
Conclusion

Data mining is a very crucial step of the KDD process.

For further reading aboud KDD and data mining ,please check this link.

Source: http://nocodewebscraping.com/difference-data-mining-kdd/

Data Discovery vs. Data Extraction

Data Discovery vs. Data Extraction

Looking at screen-scraping at a simplified level, there are two primary stages involved: data discovery and data extraction. Data discovery deals with navigating a web site to arrive at the pages containing the data you want, and data extraction deals with actually pulling that data off of those pages. Generally when people think of screen-scraping they focus on the data extraction portion of the process, but my experience has been that data discovery is often the more difficult of the two.

The data discovery step in screen-scraping might be as simple as requesting a single URL. For example, you might just need to go to the home page of a site and extract out the latest news headlines. On the other side of the spectrum, data discovery may involve logging in to a web site, traversing a series of pages in order to get needed cookies, submitting a POST request on a search form, traversing through search results pages, and finally following all of the "details" links within the search results pages to get to the data you're actually after. In cases of the former a simple Perl script would often work just fine. For anything much more complex than that, though, a commercial screen-scraping tool can be an incredible time-saver. Especially for sites that require logging in, writing code to handle screen-scraping can be a nightmare when it comes to dealing with cookies and such.

In the data extraction phase you've already arrived at the page containing the data you're interested in, and you now need to pull it out of the HTML. Traditionally this has typically involved creating a series of regular expressions that match the pieces of the page you want (e.g., URL's and link titles). Regular expressions can be a bit complex to deal with, so most screen-scraping applications will hide these details from you, even though they may use regular expressions behind the scenes.

As an addendum, I should probably mention a third phase that is often ignored, and that is, what do you do with the data once you've extracted it? Common examples include writing the data to a CSV or XML file, or saving it to a database. In the case of a live web site you might even scrape the information and display it in the user's web browser in real-time. When shopping around for a screen-scraping tool you should make sure that it gives you the flexibility you need to work with the data once it's been extracted.

Source: http://ezinearticles.com/?Data-Discovery-vs.-Data-Extraction&id=165396

Best Alternative For Linkedin Data Scraping

Best Alternative For Linkedin Data Scraping

When I started my career in sales, one of the things that my VP of sales told me is that ” In sales, assumptions are the mother of all f**k ups “. I know the F word sounds a bit inappropriate, but that is the exact word he used. He was trying to convey the simple point that every prospect is different, so don’t guess, use data to come up with decisions.

I joined Datahut and we are working on a product that helps sales people. I thought I should discuss it with you guys and take your feedback.

Let me tell you how the idea evolved itself. At Datahut, we get to hear a lot of problems customers want to solve. Almost 30 percent of all the inbound leads ask us to help them with lead generation.

Most of them simply ask, “Can you scrape Linkedin for me”?

Every time, we politely refused.

But not anymore, we figured out a way to solve their problem without scraping Linkedin.

This should raise some questions in your mind.

1) What problem is he trying to solve?– Most of the time their sales team does not have the accurate data about the prospects. This leads to a total chaos. It will end up in a waste of both time and money by selling the leads that are not sales qualified.

2) Why do they need data specifically from Linkedin? – LinkedIn is the world’s largest business network. In his view, there is no better place to find leads for his business than Linkedin. It is right in a way.

3) Ok, then what is wrong in scraping Linkedin? – Scraping Linkedin is against its terms and it can lead to legal issues. Linkedin has an excellent anti-scraping mechanism which can make the scraping costly.

4) How severe is the problem? – The problem has a direct impact on the revenues as the productivity of the sales team is too low. Without enough sales, the company is a joke.

5) Is there a better way? – Of course yes. The people with profiles in LinkedIn are in other sites too. eg. Google plus, CrunchBase etc. If we can mine and correlate the data, we can generate leads with rich information. It will have better quality than scraping LinkedIn.

6) What to do when the machine intelligence fails? – We have to use human intelligence. Period!

Datahut is working on a platform that can help you get leads that match your ideal buyer persona. It will be a complete Business intelligence platform powered by machine and human intelligence for an efficient lead research & discovery.We named it Leadintel. We’ve also established some partnerships that help to enrich the data and saves the trouble of lawsuits.

We are opening our platform for beta users. You can request an invitation using the contact form. What do you think about this? What are your suggestions?

Thanks for reading this blog post. Datahut offers affordable data extraction services (DaaS) . If you need help with your web scraping projects let us know and we will be glad to help.

Source:http://blog.datahut.co/best-alternative-for-linkedin-data-scraping/

Content Scrapers – How to Find Out Who is Stealing Your Content & What to Do About It

If you have been blogging for a while, chances are you are familiar with content scrapers. Content scrapers are websites that steal your content for their own blogs without your permission. Some content scrapers will just copy the content off of your blog, but most use automated software that takes the content from your RSS feed and posts your content to their site like it is a new post.

In this post, we are going to look at some potential link building benefits to content scrapers, how to find out what sites are scraping your content, and what you can do if you want to either benefit from the linking standpoint or have them take it down.

Linking Benefits of Content Scrapers

Last week, I was happy to see that I was listed in ProBlogger’s 20 Bloggers to Watch in 2012. Within 24 hours, I received a notification in my WordPress dashboard that a page on my blog had been linked to in the post on ProBlogger’s site.

After receiving the original notification from the ProBlogger post, I also received another 18 trackbacks from sites that had stolen the content in their post verbatim. Trackbacks are WordPress’ way of letting you know that another website has linked to a post on your blog. In this case, these 18 sites had posted the content exactly like the original post – with the links back to my blog still intact.

It was then that I started contemplating the potential link building benefits of content scrapers. These are not by any means quality links – the highest Google PageRank was a PR 2 domain, many were stealing content in a variety of languages, and one even had the nerve to use some kind of redirection script to take away the link juice of outgoing links! So while these links didn’t have the same authority that the original post had, they still count as links.

How to Catch Content Scrapers

Unfortunately, unless you want to continuously search for your post titles in Google, you’ll only be able to easily track down sites that keep your in-content links active. If you want to know what websites are scraping your content, here are a few tips to sniff them out.

Copyscape

Copyscape is a simple search engine that allows you to enter the URL of your content to find out if there are duplicates of it on the Internet. You can get a few results using their free search, or you can pay for a premium account to check up to 10,000 pages on your site and more.

Trackbacks

The first way is through your trackbacks in WordPress (as shown in the image above). Many of these will show up in the spam folder if you use Akismet. The key to getting trackbacks to appear from content scrapers is to always include links to other posts in your content. Be sure those links have great anchor text too, if you’re going for a little extra link juice. And even if you are not, internal linking with strong anchor text is good for your on-site optimization too!

Anyone thinking about link building benefits at this point is probably noting the sheer volume of links from these sites, some of which are content scrapers. Essentially any site that is linking to a lot of your posts that isn’t a social network, social bookmarking site, or a die-hard fan who just loves linking to you is potentially a content scraper. You’ll have to go to their website to be sure. To find your links on their site, click on one of the domains to see the details of what pages on your site they are linking to specifically.

You can see here that they are just blatantly copying my posts titles. When I visited one of the links, sure enough, they are copying my entire posts in their full glory onto their site.

Google Alerts

If you don’t post often or want to keep up with any mentions of your top blog posts on other websites, you can create a Google Alert using the exact match for your post’s title by putting the title in quotation marks.

I deliver all of my Google Alerts to an RSS feed so I can manage them in Google Reader, but you can also have them delivered regularly by email. You’ll even get an instant preview of the types of results you will get.

How to Get Credit for Scraped Posts

If you use WordPress, then you definitely want to try out the RSS footer plugin. This plugin allows you to place a custom piece of text at the top or bottom of your RSS feed content.
As you can see, even if you aren’t using it for the purpose of getting credit back to your posts when content thieves steal it, you can still use it for a little extra bit of advertising with the possible benefit of people who subscribe to your RSS feed clicking through to your website or social profiles. And when someone does scrape your content from your RSS feed, it shows up there too

So in the event that someone finds your scraped content, they will hopefully notice the credit before assuming it was created by the blog that stole it. If you don’t have WordPress, you can simply include a note at the top or bottom of your content that includes the same information.

How to Stop Content Scrapers

If you’re not interested in anyone copying your content, then you have a few options to choose from. You can start by contacting the site that is stealing your content and sending them a notice that you want all of your content removed immediately. You can do this through the site’s contact form, email address, or post it to any social accounts they list.

If there is no contact information on the website stealing your content, you can do a Whois Lookup to (hopefully) find out who owns the domain.

If it is not privately registered, you should find an administrative contact’s email address. If not, you should at least see the domain registrar which, in this case, is GoDaddy and/or the hosting company for the website which, in this case, is HostGator. You can try to contact both companies (HostGator has a DMCA form and GoDaddy has an email) and let them know that the domain in question is stealing copyrighted content in hopes that the website will be suspended or removed.

You can also visit the DMCA and use their takedown services to remove anyone who is copying your photos, video, audio, blog, or other content. They even offer a WordPress plugin to incorporate a DMCA protected badge on your site to warn potential thieves.

Have you ever dealt with content scrapers and thieves? Do you leave it alone for the link benefits, or do you fight back? What other tools, services, or other preventative tactics do you use to block content scrapers? Please share your thoughts and experiences in the comments!

Source URL : https://blog.kissmetrics.com/content-scrapers/

Web Data Scraping: Practical Uses

Whether in the form of media, text or data in diverse other formats—the internet serves to be a huge storehouse of the world’s information. While browsing for commercial or business needs alike, users are exposed to numerous web pages that contain data in just about every form. Even though access to such data is extremely critical for garnering success in the contemporary world, unfortunately most of it is not open. More often than not, business websites restrict the accessibility options to such data and do not allow visitors to save or display them for reuse on their local storage devices, or onto their own websites.  This is where web data extraction tools come in handy.

Read on for a closer look into some of the common areas of data scraping usage.

• Gathering of data from diverse sources for analysis: In case a business necessitates the collection and analysis of data specific to certain categories from multiple websites, then it helps refer to web data integration experts or those related to the field of data scraping linked with categories like industrial equipment, real estate, automobiles, marketing, business contacts, electronic gadgets and so forth.

• Collection of data in different formats: Different websites are known to publish information and structured data in different formats. So, it may not be possible for organizations to see all the required data a one place, at any given time. Data scrapers allow the extraction of information spanning across multiple pages under various sections, on to a single database or spreadsheet.  This makes it easy for users to analyze (or visualize) the data.

• Helps Research: Data is an important and integral part of all kinds of research – marketing, academic or scientific. A data scraper helps in gathering structured data with ease.

• Market analysis for businesses: Companies that cater to products or services connected to specific domains require comprehensive data of products and services that are of similar kind, and which have a tendency of appearing in the market on a daily basis.

Web scraping software solutions from reputed companies are successful in keeping a constant watch on this kind of data and allow users to get access required information from diverse sources – all at the click of a button.
Go for data extraction to take your business to the next levels of success – you will not be disappointed.

Source URL : http://www.3idatascraping.com/web-data-scraping-practical-uses.php

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 URL :   http://yellowpagesdatascraping.blogspot.in/2015/06/data-scraping-what-are-hand-scraped.html

Increasing Accessibility by Scraping Information From PDF

You may have heard about data scraping which is a method that is being used by computer programs in extracting data from an output that comes from another program. To put it simply, this is a process which involves the automatic sorting of information that can be found on different resources including the internet which is inside an html file, PDF or any other documents. In addition to that, there is the collection of pertinent information. These pieces of information will be contained into the databases or spreadsheets so that the users can retrieve them later.

Most of the websites today have text that can be accessed and written easily in the source code. However, there are now other businesses nowadays that choose to make use of Adobe PDF files or Portable Document Format. This is a type of file that can be viewed by simply using the free software known as the Adobe Acrobat. Almost any operating system supports the said software. There are many advantages when you choose to utilize PDF files. Among them is that the document that you have looks exactly the same even if you put it in another computer so that you can view it. Therefore, this makes it ideal for business documents or even specification sheets. Of course there are disadvantages as well. One of which is that the text that is contained in the file is converted into an image. In this case, it is often that you may have problems with this when it comes to the copying and pasting.

This is why there are some that start scraping information from PDF. This is often called PDF scraping in which this is the process that is just like data scraping only that you will be getting information that is contained in your PDF files. In order for you to begin scraping information from PDF, you must choose and exploit a tool that is specifically designed for this process. However, you will find that it is not easy to locate the right tool that will enable you to perform PDF scraping effectively. This is because most of the tools today have problems in obtaining exactly the same data that you want without personalizing them.

Nevertheless, if you search well enough, you will be able to encounter the program that you are looking for. There is no need for you to have programming language knowledge in order for you to use them. You can easily specify your own preferences and the software will do the rest of the work for you. There are also companies out there that you can contact and they will perform the task since they have the right tools that they can use. If you choose to do things manually, you will find that this is indeed tedious and complicated whereas if you compare this to having professionals do the job for you, they will be able to finish it in no time at all. Scraping information from PDF is a process where you collect the information that can be found on the internet and this does not infringe copyright laws.

 Source  URL : http://ezinearticles.com/?Increasing-Accessibility-by-Scraping-Information-From-PDF&id=4593863

Web Scraping to Create Open Data

Open data is the idea that some data should be freely available to everyone to use and republish as they wish, without restrictions from
copyright, patents or other mechanisms of control.

My first experience with open data was in the year 2010. I wanted to create a better app for Bicing, the local bike sharing system in
Barcelona. Their website was a nightmare to use and I was tired of needing to walk to each station, trying to guess which ones had bicycles.
There was no app for Android, other than a couple of unofficial attempts that didn’t work at all.

I began as most would; I searched the internet and found a library named python-bicing that was somehow able to retrieve station and
bike information. This was my first time using Python and, after some investigation, I learned what the code was doing: accessing the
official website, parsing the JavaScript that generated their buggy map and giving back a nice chunk of Python objects that represented
bike share stations.

This I learned was called web scraping. It was like I had figured out a magic trick that would allow me to always be able to access the data I
needed without having to rely on faulty websites.

The rise of OpenBicing and CityBikes

Shortly after, I launched OpenBicing, an Android app for the local bike sharing system in Barcelona, together with a backend that used
python-bicing. I also shared a public API that provided this information so that nobody else had to do the dirty work ever again.

Since other cities were having the same problem, we expanded the scope of the project worldwide and renamed it CityBikes. That was 6
years ago.

To date, CityBikes is the most comprehensive and widely used open API for bike sharing information, with support for over 400 cities
worldwide. Our API processes around 10 requests per second and we scrape each of the 418 feeds about every three minutes. Making our
core library available for anyone to contribute has been crucial in maintaining and adding coverage for all of the supported systems.

The open data fallacy

We are usually regarded as “an open data project” even though less than 10% of our feeds come from properly licensed, documented and
machine-readable feeds. The remaining 90% is composed of 188 feeds that are machine-readable, but not licensed nor documented and
230 that are entirely maintained by scraping HTML pages.

North American BikeShare Association) recently published GBFS (General Bikeshare Feed Specification). This is clearly a step in the right
direction, but I can’t help but look at the almost 60% of services we currently support through scraping and wonder how long it will take the
remaining organizations to release their information, if ever. This is even more the case considering these numbers aren’t even taking into
account worldwide coverage.

Over the last few years there has been a progression by transportation companies and city councils toward providing their information as
“open data”. Directive 2003/98/EC encourages EU member states to release information regarding public services.

Yet, in most cases, there’s little action in enforcing Public Private Partnerships (PPP) to release their public information under a non-
restrictive license or even to transfer ownership of the data to city councils to be included in their open data portals.

Even with the increasing number of companies and institutions interested in participating in open data, by no means should we consider
open data a reality or something to be taken for granted. I firmly believe in the future and benefits of open data, I have seen them
happening all around CityBikes, but as technologists we need to stress the fact that the data is not out there yet.

The benefits of open data

When I started this project, I sought to make a difference in Barcelona. Now you can find tons of bike sharing apps that use our API on all
major platforms. It doesn’t matter that these are not our own apps. They are solving the same problem we were trying to fix, so their
success is our success.

Besides popular apps like Moovit or CityMapper, there are many neat projects out there, some of which are published under free software
licenses. Ideally, a city council could create a customization of any of these apps for their own use.

Most official applications for bike sharing systems have terrible ratings. The core business of transportation companies is running a service,

so they have no real motivation to create an engaging UI or innovate further. In some cases, the city council does not even own the rights to
the data, being completely at the mercy of the company providing the transportation service.

Open data over apps

When providing public services, city councils and companies often get lost in what they should offer as an aid to the service. They focus on
a nice map or a flashy application, rather than providing the data behind these service aids. Maps, apps, and websites have a limited focus
and usually serve a single purpose. On the other hand, data is malleable and the purest form of representation. While you can’t create
something new from looking and playing with a static map (except, of course, if you scrape it), data can be used to create countless
different iterations. It can even provide a bridge that will allow anyone to participate, improve and build on top of these public services.

Wrap Up

At this point, you might wonder why I care so much about bike sharing. To me it’s not about bike sharing anymore. CityBikes is just too
good of an open data metaphor, a simulation in which public information is freely accessible to everyone. It shows the benefits of open
data and the deficiencies that arise from the lack thereof.

We shouldn’t have to create open data by scraping websites. This information should be already available, easily accessed and provided in
a machine-readable format from the original providers, be they city councils or transportation companies. However, until there’s another
option, we’ll always have scraping.


Source : https://blog.scrapinghub.com/2016/03/30/web-scraping-to-create-open-data/

Web Scraping – Ethical Data Collection Activity or an Illegal Practice?

Abiding by the definition, web scrapping is a method to extract data from website. There can be different reasons to perform this task, such as for reporting, market research, to determine share indexes, know website updates, product rate updates, to monitor data, and so on. Besides these, data theft is another of the prominent motives behind web data extraction, which ultimately holds the use of a web scraper as unethical and at times, illegal.

Technical definition

In technical terms, data scraping is a method of collecting data from a website through specific software. These software programs or web scrapers give the website owners the impression of human web surfing and extract a big volume of data, which is usually difficult for any user visitor to access manually. The apps simulate human exploration of online data by embedding web browsers, or implementing HTTP to fulfill the cause of data extractors.

Relation with data mining

Usually, data mining refers to analyzing data from varied perspectives and transforming it to meaningful information that could help in boosting sales or mitigating financial risks in a business. As for web scraping, it involves extraction of analytical data from the web. At present, web scrapping comprises major source of data extraction carried out by data miners. This is because almost everything is now available online and for any data miner, this resource is no less than a gold mine.

The web scraping process

In this data scraping method, the experts look out for tricks to format the URLs into pages that include the usable information. The web scrapers then parse the DOM tree to extract data from the website. In simple language, the web scrapers process the semi-structured or unstructured data pages of the desired website and then convert the resulting data into a well structured form. The users can harvest or modify the structured data in a better manner.

Web scraping – legal or unethical?

It solely relies on your intentions, whether you are doing this activity in the interest of the masses or just wish to satisfy your personal interests. If it is for a goodwill, such as to research on share index to predict the market situation in the coming days, it is fine. Another positive example could be to identify the trend of market and suggest a client on viable business boosting methods accordingly.

However, if you are doing web scraping for personal gratification then it may well be termed as intrusion into one’s personal data. For example, if you are hacking into the database of a university to steal the academic articles and using them in your own project. Any such instance is definitely an act of stealth and may accompany relevant punishment. Concisely, to get hold of someone’s creative work for individual gains is unethical. Such people also deploy several bots to for data scraping or spinning, which in turn choke the search engine results and hardly useful to the internet.

Considerations that deem web scraping illegal

Generally, web scraping is illegal in two instances:

1. When you violate the terms and conditions of the service of the concerned website:

Most of the data-oriented websites disallow data scraping. Hence, if you are trying to extract data from that website, the owner has all the rights to sue you on the offense of breach of contract.

2. When you publish scraped content:

This is yet another condition that may delve you into violating the right of the copyright holders. If you are only scraping the content for fair use, it may be permissible. However, companies often hold all the publishing rights and may file suit against you if you publish their data without their permission.

Remedy to illegal web scraping

Despite running the apprehensions of getting identified, unethical web scrapers deter to steal data from websites. Hence, the web owners themselves need to be alert enough not to fall prey to such fraudulent activities. Indeed, it is your data and you won’t like it to get compromised at any cost. Just like there are many web scraping tools available online, you can also opt for applications that offer protection against web data extraction as a fruitful remedy. These software safeguard your website content from hacking attacks such as bots, denial of service, brute force, session opening and transaction anomalies, and more.

Summary: Technology has two facets – good and bad. It depends on us which one to adopt; the same holds in the case of web scraping as well. We should make sure to use this innovation for the benefit of society and not to steal away some one’s creativity, which is indeed unethical and at times, illegal

Source : http://www.web-parsing.com/blog/ethical-data-collection-activity-or-an-illegal-practice

Taking a cue from the Ryanair screen scraping judgment

Screen scraping is the best way to aggregate web data much faster than a human possibly can. However, is there any such thing known as ethical web scraping?

Well it’s not scraping in itself that is good or bad. What matters is how you use the scraped data. It would be extremely unethical to steal data, republish it or use it to cause harm to a business. This was clearly established when the EU passed a judgment in favour of Ryanair.

The EU’s highest court passed a judgment in favour of Ryan air, and this will positively prevent people from scraping and using others data in an unethical manner. Ryanair had claimed that PR Aviation scraped its data regarding the flight scheduled and then used it to allow people book Ryanair flights via the PR Aviation website and this is clearly an infringement of database rights.

Source:http://www.habiledata.com/blog/taking-cue-ryanair-screen-scraping-judgment/