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.


Article Source: http://EzineArticles.com/3860679

Data Collection, Just Another Way To Gather Information

Data collection just does not help the companies to launch new products or know about the public reaction to a specific issue, it is a very useful tool for statistical inferences, once the collected data is compiled. The process of data collection is the third step of the six step market research processes. Data collection can be done in two ways involving various technicalities. In this article, we shall give a brief overview of the same.

Data collection can be done in two ways - secondary data and primary data. Secondary data collection involves is the information available in books, journals, previous researches or studies and the Internet. It basically involves making use of the data already present to build or substantiate a concept.

On the other hand, primary data collection is the process of data collection through questionnaire by directly asking respondents of their opinions. Forming the right questionnaire is the most important aspect of data collection. The researcher conducting the data collection just has to be aware of the process. He should have a clear idea about the information sought by the concerned party.

Besides, the data collection officer should be able to construct the questionnaire in such a way so as to elicit the responses needed. Having constructed the questionnaire the researcher should identify the target sample. To illustrate the point clearly, we shall look into the following example.

Suppose, data collection is aimed from an area A, then, if all the residents of the data are given the questionnaire, it is called a census or in other words data collection is done from all the individuals of the specified area. One of the most common examples of data collection done by the government is census. For example the population census conducted by the US Census Bureau every ten years. On the other hand, if only twenty or thirty percent of the population living in area A are given the questionnaire, the mode of data collection would be called sampling.

The data collected from the target sample with a well-defined questionnaire will project the response of the entire population living in the area. Data collected from a sample helps to control the cost and time spent on collecting data from the population. Sample is a part of population.

Data collection just gets easier from the target sample with the help of a pretested questionnaire, which is later analyzed using statistical tests like ANOVA, Chi Square test and so on. These tests help the researcher to infer the result obtained from the data collection.

Market research/data collection is a fast growing and lucrative career option now days. One has to undertake a course in marketing, statistics and research before starting out. It is indeed very important to have a through understanding of various concepts and the theories related. Some basic terminologies related to data collection are: census, incidence, sample, population, parameters, sampling frames and so on.

Source: http://ezinearticles.com/?Data-Collection,-Just-Another-Way-To-Gather-Information&id=853158

How Easily Can You Extract Data From Web

With tech advancements taking the entire world by a storm, every sector is undergoing massive transformations. As far as the business arena is concerned, the rise of big data and data analytic is playing a crucial part in operations. Big data and data analysis is the best way to identify customer interests. Businesses can gain crystal clear insights into consumers’ preferences, choices, and purchase behaviours, and that’s what leads to unmatched business success. So, it’s here that we come across a crucial question. How do enterprises and organizations leverage data to gain crucial insights into consumer preferences? Well, data extraction and mining are the two significant processes in this context. Let’s take a look at what data extraction means as a process.

Decoding data extraction

Businesses across the globe are trying their best to retrieve crucial data. But, what is it that’s helping them do that? It’s here that the concept of data extraction comes into the picture. Let’s begin with a functional definition of this concept. According to formal definitions, ‘data extraction’ refers to the retrieval of crucial information through crawling and indexing. The sources of this extraction are mostly poorly-structured or unstructured data sets. Data extraction can prove to be highly beneficial if done in the right way. With the increasing shift towards online operations, extracting data from the web has become highly important.

The emergence of ‘scraping’

The act of information or data retrieval gets a unique name, and that’s what we call ‘data scraping.’ You might have already decided to pull data from 3rd party websites. If that’s what it is, then it’s high time to embark on the project. Most of the extractors will begin by checking the presence of APIs. However, they might be unaware of a crucial and unique option in this context.

Automatic data support

Every website lends virtual support to a structured data source, and that too by default. You can pull out or retrieve highly relevant data directly from the HTML. The process is termed as ‘web scraping’ and can ensure numerous benefits for you. Let’s check out how web scraping is useful and awesome.

Any content you view is ready for scraping

All of us download various stuff throughout the day. Whether it is music, important documents or images, downloads seem to be regular affairs. When you are successful in downloading any particular content of a page, it means the website offers unrestricted access to your browser. It won’t take long for you to understand that the content is programmatically accessible too. On that note, it’s high time to work out effective reasons that define the importance of web scraping. Before opting for RSS feeds, APIs, or other conventional data extraction methods, you should assess the benefits of web scraping. Here’s what you need to know in this context.

Website vs. APIs: Who’s the winner?

Site owners are more concerned about their public-facing or official websites than the structured data feeds. APIs can change, and feeds can shift without prior notifications. The breakdown of Twitter’s developer ecosystem is a crucial example for this.

So, what are the reasons for this downfall?

At times, these errors are deliberate. However, the crucial reasons are something else. Most of the enterprises are completely unaware of their structured data and information. Even if the data gets damaged, altered, or mangled, there’s no one to care about it.

However, that isn’t what happens with the website. When an official website stops functioning or delivers poor performance, the consequences are direct and in-your-face. Quite naturally, developers and site owners decide to fix it almost instantaneously.

Zero-rate limiting

Rate-limiting doesn’t exist for public websites. Although it’s imperative to build defences against access automation, most of the enterprises don’t care to do that. It’s only done if there are captchas on signups. If you aren’t making repeated requests, there are no possibilities of you being considered as a DDOS attack.

In-your-face data

Web scraping is perhaps the best way to gain access to crucial data. The desired data sets are already there, and you won’t have to rely on APIs or other data sources for gaining access. All you need to do is browse the site and find out the most appropriate data. Identifying and figuring out the basic data patterns will help you to a great extent.

Unknown and Anonymous access

You might want to gather information or collect data secretly. Simply put, you might wish to keep the entire process highly confidential. APIs will demand registrations and give you a key, which is the most important part of sending requests. With HTTP requests, you can stay secure and keep the process confidential, as the only aspects exposed are your site cookies and IP address. These are some of the reasons explaining the benefits of web scraping. Once you are through with these points, it’s high time to master the art of scraping.

Getting started with data extraction

If you are already eager to grab data, it’s high time you work on the blueprints for the project. Surprised? Well, data scraping or rather web data scraping requires in-depth analysis along with a bit of upfront work. While documentations are available with APIs, that’s not the case with HTTP requests. Be patient and innovative, as that will help you throughout the project.

2. Data fetching

Begin the process by looking for the URL and knowing the endpoints. Here are some of the pointers worth considering:

- Organized information: You must have an idea of the kind of information you want. If you wish to have it in an organized manner, rely on the navigation offered by the site. Track the changes in the site URL while you click through sections and sub-sections.
- Search functionality: Websites with search functionality will make your job easier than ever. You can keep on typing some of the useful terms or keywords based on your search. While doing so, keep track of URL changes.
- Removing unnecessary parameters: When it comes to looking for crucial information, the GET parameter plays a vital role. Try looking for unnecessary and undesired GET parameters in the URL, and removing them from the URL. Keep the ones that’ll help you load the data.

2. Pagination comes next

While looking for data, you might have to scroll down and move to subsequent pages. Once you click to Page 2, ‘offset=parameter’ gets added to the selected URL. Now, what is this function all about? The ‘offset=parameter’ function can represent either the number of features on the page or the page-numbering itself. The function will help you perform multiple iterations until you attain the “end of data” status.

Trying out AJAX

Most of the people nurture certain misconceptions about data scraping. While they think that AJAX makes their job tougher than ever, it’s actually the opposite. Sites utilising AJAX for data-loading ensures smooth data scraping. The time isn’t far away when AJAX will return along with JavaScript. Pulling up the ‘Network’ tab in Firebug or Web Inspector will be the best thing to do in this context. With these tips in mind, you will have the opportunity to get crucial data or information from the server. You need to extract the information and get it out of the page markup, which is the most difficult or tricky part of the process.

Unstructured data issues

When it comes to dealing with unstructured data, you will need to keep certain crucial aspects in mind. As stated earlier, pulling out the data from page markups is a highly critical task. Here’s how you can do it:

1. Utilising the CSS hooks

According to numerous web designers, the CSS hooks happen to be the best resources for puling data. Since it doesn’t involve numerous classes, CSS hooks offer straightforward data scraping.

2. Good HTML Parsing

Having a good HTML library will help you in ways more than one. With the help of a functional and dynamic HTML parsing library, you can create several iterations as and when you wish to.
Knowing the loopholes

Web scraping won’t be an easy affair. However, it won’t be a hard nut to crack either. While knowing the crucial web scraping tips is necessary, it’s also imperative to get an idea of the traps. If you have been thinking about it, we have something for you!

- Login contents: Contents that require you to login might prove to be potential traps. It reveals your identity and wreaks havoc on your project’s confidentiality.

- Rate limiting: Rate limiting can affect your scraping needs both positively and negatively, and that entirely depends on the application you are working on.

Source:-https://www.promptcloud.com/blog/how-easy-is-data-extraction

Why Customization is the Key Aspect of a Web Scraping Solution

Why Customization is the Key Aspect of a Web Scraping Solution

Every web data extraction requirement is unique when it comes to the technical complexity and setup process. This is one of the reasons why tools aren’t a viable solution for enterprise-grade data extraction from the web. When it comes to web scraping, there simply isn’t a solution that works perfectly out of the box. A lot of customization and tweaking goes into achieving a stable setup that can extract data from a target site on a continuous basis.

Customization web scraping service

This is why freedom of customization is one of the primary USPs of our web crawling solution. At PromptCloud, we go the extra mile to make data acquisition from the web a smooth and seamless experience for our client base that spans across industries and geographies. Customization options are important for any web data extraction project; Find out how we handle it.

The QA process

The QA process consists of multiple manual and automated layers to ensure only high-quality data is passed on to our clients. Once the crawlers are programmed by the technical team, the crawler code is peer reviewed to make sure that the optimal approach is used for extraction and to ensure there are no inherent issues with the code. If the crawler setup is deemed to be stable, it’s deployed on our dedicated servers.

The next part of manual QA is done once the data starts flowing in. The extracted data is inspected by our quality inspection team to make sure that it’s as expected. If issues are found, the crawler setup is tweaked to weed out the detected issues. Once the issues are fixed, the crawler setup is finalized. This manual layer of QA is followed by automated mechanisms that will monitor the crawls throughout the recurring extraction, hereafter.

Customization of the crawler

As we previously mentioned, customization options are extremely important for building high quality data feeds via web scraping. This is also one of the key differences between a dedicated web scraping service and a DIY tool. While DIY tools generally don’t have the mechanism to accurately handle dynamic and complex websites, a dedicated data extraction service can provide high level customization options. Here are some example scenarios where only a customizable solution can help you.

File download

Sometimes, the web scraping requirement would demand downloading of PDF files or images from the target sites. Downloading files would require a bit more than a regular web scraping setup. To handle this, we add an extra layer of setup along with the crawler which will download the required files to a local or cloud storage by fetching the file URLs from the target webpage. The speed and efficiency of the whole setup should be top notch for file downloads to work smoothly.

Resize images

If you want to extract product images from an Ecommerce portal, the file download customization on top of a regular web scraping setup should work. However, high resolution images can easily hog your storage space. In such cases, we can resize all the images being extracted programmatically in order to save you the cost of data storage. This scenario requires a very flexible crawling setup, which is something that can only be provided by a dedicated service provider.

Extracting key information from text

Sometimes, the data you need from a website might be mixed with other text. For example, let’s say you need only the ZIP codes extracted from a website where the ZIP code itself doesn’t have a dedicated field but is a part of the address text. This wouldn’t be normally possible unless you write a program to be introduced into the web scraping pipeline that can intelligently identify and separate the required data from the rest.
Extracting data points from site flow even if it’s missing in the final page

Sometimes, not all the data points that you need might be available on the same page. This is handled by extracting the data from multiple pages and merging the records together. This again requires a customizable framework to deliver data accurately.

Automating the QA process for frequently updated websites

Some websites get updated more of than others. This is nothing new; however, if the sites in your target list get updated at a very high frequency, the QA process could get time-consuming at your end. To cater to such a requirement, the scraping setup should run crawls at a very high frequency. Apart from this, once new records are added, the data should be run through a deduplication system to weed out the possibility of duplicate entries in the data. We can completely automate this process of quality inspection for frequently updated websites.

Source:https://www.promptcloud.com/blog/customization-is-the-key-aspect-of-web-scraping-solution

Web Scraping using Chrome Scraper Extension

Do you want to get data from a web page or website to CSV or Excel Spreadsheet? The answer is web scraping. There are number of web scraping software and services available in the market like Visual Web Ripper, Mozenda, Kimono Labs, Outwit Hub, ScraperWiki and Automation Anywhere etc. for web data extraction. These all tools and services are paid and not easy to use for non-technical persons. Now I am going to discuss another method of doing web scraping that is easy to use and free.  There are various Google Chrome browser extensions available at Google Web Store (https://chrome.google.com/webstore/category/apps) using that we can do screen scraping/web scraping.

1. Web scraper
Official Website: http://www.webscraper.io

Install it by visiting following link:

https://chrome.google.com/webstore/detail/scraper/mbigbapnjcgaffohmbkdlecaccepngjd

Web Scraper is a chrome extension for scraping data out of web pages to Excel Spreadsheet or database. It allows you to create a plan/sitemap. According to that plan/sitemap a website is traversed and the data is extracted. The extracted data can be exported to CSV or stored in CouchDB. It also supports scraping from multiple pages with pagination. You can use Web Scraper for scraping multiple types of data like text, tables, images, links and more. It also supports web data extraction from dynamic web pages built up with modern web technologies like JavaScript and AJAX.

2. Data Miner
Install DataMiner by visiting following link:

https://chrome.google.com/webstore/detail/dataminer/nndknepjnldbdbepjfgmncbggmopgden

DataMiner is a standalone chrome browser plugin for extracting data from the websites. Later on extracted data can be exported to Microsoft Excel spreadsheets or Google Sheets.

Using DataMiner extension, you can scrape data from tables and lists on the websites and easily export them into CSV file or Microsoft Excel. It also supports XPath selectors. You can use it for scraping emails, Google search results, HTML tables etc.



3. Screen Scraper:
Install it by visiting following link:

https://chrome.google.com/webstore/detail/screenscraper/pfegffhjcgkneoemnlniggnhkfioidjg

Screen Scraper is another chrome scraper as it name suggest is a Chrome browser extension/plugin for screen scraping. Screen scraping is the process of automatically scraping/extracting information from websites. Later on, Scraped information can be downloaded as a CSV file or JSON file. It supports Element Selectors and Xpath Selectors method.

4. iMacro
Official Website of iMacro: http://imacros.net/

Install iMacro it by visiting following link:

https://chrome.google.com/webstore/detail/imacros-for-chrome/cplklnmnlbnpmjogncfgfijoopmnlemp?hl=en

iMacro is a macro recorder for your Google Chrome browser. Macro recorder is a piece of tool that records user actions. It allows users to record repetitious tasks on the web and replay it at later time. It is useful tool for web automation, data extraction and web testing. Using iMacros you can remember passwords, fill out web forms, download files and possibilities are endless. iMacros is useful to Web developers for web regression testing, performance testing and web transaction monitoring. To use iMacros you just need to record the task once and save it in your machine next time when you need to perform the same task you need not repeat the same task again and again. iMacro plugin comes for Chrome, Firefox and Internet Explorer too.

Source url :-http://webdata-scraping.com/web-scraping-using-chrome-scraper-extension/

Six Tools to Make Data Scraping More Approachable

What is data scraping?

Data scraping is a technique in which a computer program/software extracts data from a website, so it can be used for other purposes.Scraping may sound a little intimidating, but with the help of scraping tools, the process can be a lot more approachable. The tools are used to capture data you need from specific web pages quicker and easier.

Let your computer do all the work

It takes only a few minutes for systems to recognize each others codes even in huge databases. Computers have their own language and that is why some of these tools make it easier to pull and format information in a way that is simpler for people to reuse.

Here is a list of some data scraping tools:

1.Diffbot

What makes this tool so likable is the business-friendly approach. Tools like Diffbot are perfect for searching through competitors work and the performance of your own webpage. Get product data from images, articles, discussions, web crawling tools and process websites. If you like how this sounds, see for yourself and sign up for their 14-day free trial.


2.Import.io

Import.io can help you easily get the information from the any source on the web. This tool can get your data in less than 30 seconds, depending on how complicated the data is and its structure in the website.  It can also be used for multiple URL scraping at once.

Here is one example: Which city of California based organizations try to hire the most through Linkedin? Check this list of jobs available in linkedin, download a csv file, sort from A to Z the cities and voila – San Francisco it is. Did you know that it’s for free?

3.Kimono

Kimono gives you easy access to APIs created for various web pages. No need to write any code or install any software to extract data. Simply paste the URL into the website or use a bookmark. Select how often you want the data to be collected and it saves it for you.

4.ScraperWiki

ScraperWiki gives you two choices – extract data from PDFs or build your own scraping tool in PHP, Ruby and Python language. It is meant for more experienced users and offers consulting (a paid service) if you need to learn some coding to get what you need. The first two PDF files are analyzed and reorganized for free, afterwards it’s a paid solution.

5.Grabz.it

Yes, Grabz.it does grab something. It takes information that is meaningful to you. The tool extracts data from the web, then converts videos into animated GIF that you can use on your website or application. This tool was made for those who code in ASP.NET, Java, JavaScript, Node.js, Perl, PHP, Python and Ruby languages.

6.Python

If programming is the language you love the most, then use Python to build your own scraping tool and get the data from a page you want to explore. It is particularly useful if the other tools don’t recognize the data you need.

If you haven’t used this tool before, follow this playlist of videos to learn how to use Python for web scraping:

If you want more tools, look into the Common Crawl organization. It is made for those who are interested in the data crawling world. Need a more specific tool? DMOZ and KDnuggets have lists of other tools for web data mining.

All of these tools extract information in spreadsheet formats and that is why this webinar about how to work with data in Excel can help you understand more about what to do if you desire  to supply the world with unique and beautifully data visualizations.



Source Url:-https://infogr.am/blog/six-tools-to-make-data-scraping-more-approachable/

How Artificial Intelligence Can be Applied to Web Data Extraction

How Artificial Intelligence Can be Applied to Web Data Extraction

Artificial intelligence is not a new topic at all. A lot has been written about it and it has been a popular theme of sci-fi movies from a decade ago. However, it was only recently that we started seeing AI in action. Thanks to the ever-increasing computing power, our machines are much faster and powerful now which also gives a huge boost to AI. It goes without saying that artificial intelligence requires more computing power to be truly intelligent and mimic the human brain.

artificial intelligence web data extraction

AI is finding its way into many everyday objects that we use. The voice assistant apps on your smartphone are a great example for this. Facebook’s face recognition algorithm is another example for intelligent pattern recognition technology in action. We believe that the extraction of data from web is something that humans shouldn’t be burdened with. Artificial intelligence could be the right solution to aggregating huge data sets from the web with minimal manual interference.

Artificial Intelligence VS Machine Learning

There is a stark difference between machine learning and artificial intelligence. In machine learning, you teach the machine to do something within narrowly defined rules along with some training examples. This training and rules are necessary for the machine learning system to achieve some level of success in the process it’s being taught. Whereas, in artificial intelligence, it does the teaching itself with minimal number of rules and loose training.  It can then go on to make rules for itself from the exposure that it gets, which contributes to the continued learning process. This is made possible by using artificial neural networks. Artificial neural networks and deep learning are used in artificial intelligence for speech and object recognition, image segmentation, modeling language and human motion.

Artificial intelligence in web data extraction

The web is a giant repository where data is vast and abundant. The possibilities that come with this amount of data can be ground breaking. The challenge is to navigate through this unstructured pile of information out there on the web and extract it. It takes a lot of time and effort to scrape data from the web, even with the advanced web scraping technologies. But things are about to change. Researchers from the Massachusetts Institute of Technology recently released a paper on an artificial intelligence system that can extract information from sources on the web and learn how to do it on its own.

The research paper introduces an information extraction system that can extract structured data from unstructured documents automatically. To put it simply, the system can think like humans while looking at a document. When humans cannot find a particular piece of information in a document, we find alternative sources to fill the gap. This adds to our knowledge on the topic in question. The AI system works just like this.
The AI system works on rewards and penalties

The working of this AI based data extraction system involves classifying the data with a ‘Confidence score’. This confidence score determines the probability of the classification being statistically correct and is derived from the patterns in the training data. If the confidence score doesn’t meet the set threshold, the system will automatically search the web for more relevant data. Once the adequate confidence score is achieved by extracting new data from the web and integrating it with the current document, it will deem the task successful. If the confidence score is not met, the process continues until the most relevant data has been pulled out.

This type of learning mechanism is called ‘Reinforcement learning’ and works by the notion of learning by reward. It’s very similar to how humans learn. Since there can be a lot of uncertainty associated with the data being merged together, especially where contrasting information is involved, the rewards are given based on the accuracy of the information. With the training provided, the AI learns how to optimally merge different pieces of data together so that the answers we get from the system is as accurate as possible.
AI in action

To test how well the artificial intelligence system can extract data from the web, researchers gave it a test task. The system was to analyse various data sources on mass shootings in the USA and extract the name of the shooter, number of injured, fatalities and the location. The performance was in fact mind blowing as it could pull up the accurate data the way it was needed while beating conventionally taught data extraction mechanisms by more than 10 percent.

The future of data extraction

With ever increasing need for data and the challenges associated with acquiring it, AI could be what’s missing in the equation. The research is promising and hints at a future where intelligent bots with human sight can read and crawl web documents to tell us the bits we need to know.

The AI system could be a game changer in research tasks that require a lot of manual work from humans now. A system like this will not only save time but also enables us to make use of the abundance of information out there on the web. Looking at the bigger picture, this new research is only a step towards creating the truly intelligent web spider that can master a variety of tasks just like humans rather than being focused at just one process.

Source:https://www.promptcloud.com/blog/artificial-intelligence-web-data-extraction