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 Web Crawling Can Help Venture Capital Firms

Venture capital firms are constantly on the lookout of innovative start-ups for investment. Whether you provide financial capital to early-stage start-ups in IT, software products, biotechnology or other booming industries, you will need the right information as soon as possible. In general, analysing media data to discover and validate insights is one of key areas in which analysts work. Hence, constantly monitoring popular media outlets is one of the ways VCs can deploy to spot trends. Read on to understand how web crawling can not only speed up this whole process but also improve the workflow and accuracy of insights.

What is web crawling

Web crawling simply refers to the use of automated computer programs to visit websites and extract specific bits of information. This is the same technology used by search engines to find, index and serve search results for user queries. Web crawling, as you’d have guessed is a technical and niche process. It takes skilled programmers to write programs that can navigate through the web to find and extract the needed data.

There are DIY tools, vertical specific data providers and DaaS (Data as a service) solutions that VC firms can deploy for crawling.  Although there is the option of setting up an in-house crawling setup, this isn’t recommended for Venture Capital firms. The high tech-barrier and complexity of web crawling process can lead to loss of focus for the VC firms. DaaS can be the ideal option as it’s suitable for recurring and large-scale requirements which only a hosted solution can offer.

How web crawling can help Venture Capital firms

Crawling start-up and entrepreneurship blogs using a web crawling service can help VC firms avail the much-needed data that they can use to discover new trends and validate their research. This can complement the existing research process and make it much more efficient.

1. Spot trends

Spotting new trends in the market is extremely important for venture capital firms. This helps identify the niches that have high probability of bringing in profit. Since investing in companies that have higher chances of succeeding is what Venture capital firms do, the ability to spot trends becomes an invaluable tool.

Web crawling can harvest enough data to identify trends in the market. Websites like Techcrunch and Venturebeat are great sources of start-up related news and information. Media sites like these talk about trending topics constantly. To spot trends in the market, you could use a web crawling solution to extract the article title, date and URL for the current time period and run this data through an analytics solution to identify the most used words in the article titles and URLs. Venture capital firms can then use these insights to target newer companies in the trending niches. Technology blogs, forums and communities can be great places to find relevant start-ups.

2. Validate findings

The manual research by the analysts needs to be validated before the firm can go ahead with further proceedings. Validation can be done by comparing the results of the manual work with the relevant data extracted using web crawling. This not only makes validation much easier but also helps in the weeding out process, thus reducing the possibilities of making mistakes. This can be partially automated by using intelligent data processing/visualisation tools on top the data.

3. Save time

Machines are much faster than humans. Employing web crawling to assist in the research processes in a venture capital firm can save the analysts a lot of time and effort. This time can be further invested in more productive activities like analytics, deep research and evaluation.

Source:-https://www.promptcloud.com/blog/web-crawling-for-venture-capital-firms

Data Scraping Doesn’t Have to Be Hard

All You Need Is the Right Data Scraping Partner

Odds are your business needs web data scraping. Data scraping is the act of using software to harvest desired data from target websites. So, instead of you spending every second scouring the internet and copying and pasting from the screen, the software (called “spiders”) does it for you, saving you precious time and resources.

Departments across an organization will profit from data scraping practices.

Data scraping will save countless hours and headaches by doing the following:

- Monitoring competitors’ prices, locations and service offerings
- Harvesting directory and list data from the web, significantly improving your lead generation
- Acquiring customer and product marketing insight from forums, blogs and review sites
- Extracting website data for research and competitive analysis
- Social media scraping for trend and customer analysis
- Collecting regular or even real time updates of exchange rates, insurance rates, interest rates, -mortgage rates, real estate, stock prices and travel prices

It is a no-brainer, really. Businesses of all sizes are integrating data scraping into their business initiatives. Make sure you stay ahead of the competition by effectively data scraping.

Now for the hard part

The “why should you data scrape?” is the easy part. The “how” gets a bit more difficult. Are you savvy in Python and HTML? What about JavaScript and AJAX? Do you know how to utilize a proxy server? As your data collection grows, do you have the cloud-based infrastructure in place to handle the load? If you or someone at your organization can answer yes to these questions, do they have the time to take on all the web data scraping tasks? More importantly, is it a cost-effective use of your valuable staffing resources for them to do this? With constantly changing websites, resulting in broken code and websites automatically blacklisting your attempts, it could be more of a resource drain than anticipated.

Instead of focusing on all the issues above, business users should be concerned with essential questions such as:

- What data do I need to grow my business?
- Can I get the data I need, when I want it and in a format I can use?
- Can the data be easily stored for future analysis?
- Can I maximize my staffing resources and get this data without any programming knowledge or IT assistance?
- Can I start now?
- Can I cost-effectively collect the data needed to grow my business?

A web data scraping partner is standing by to help you!

This is where purchasing innovative web scraping services can be a game changer. The right partner can harness the value of the web for you. They will go into the weeds so you can spend your precious time growing your business.

Hold on a second! Before you run off to purchase data scraping services, you need to make sure you are looking for the solution that best fits your organisational needs. Don’t get overwhelmed. We know that relinquishing control of a critical business asset can be a little nerve-wracking. To help, we have come up with our steps and best practices for choosing the right data scraping company for your organisation.

1) Know Your Priorities

We have brought this up before, but when going through a purchasing decision process we like to turn to Project Management 101: The Project Management Triangle. For this example, we think a Euler diagram version of the triangle fits best.
Data Scraping and the Project Management Triangle

In this example, the constraints show up as Fast (time), Good (quality) and Cheap (cost). This diagram displays the interconnection of all three elements of the project. When using this diagram, you are only able to pick two priorities. Only two elements may change at the expense of the third:

- We can do the project quickly with high quality, but it will be costly
- We can do the project quickly at a reduced cost, but quality will suffer
- We can do a high-quality project at a reduced cost, but it will take much longer
Using this framework can help you shape your priorities and budget. This really, in turn, helps you search for and negotiate with a data scraping company.

2) Know your budget/resources.

This one is so important it is on here twice. Knowing your budget and staffing resources before reaching out to data scraping companies is key. This will make your search much more efficient and help you manage the entire process.

3) Have a plan going in.

Once again, you should know your priorities, budget, business objectives and have a high-level data scraping plan before choosing a data scraping company. Here are a few plan guidelines to get you started:

- Know what data points to collect: contact information, demographics, prices, dates, etc.
- Determine where the data points can most likely be found on the internet: your social media and review sites, your competitors’ sites, chambers of commerce and government sites, e-commerce sites your products/competitors’ products are sold, etc.
- What frequency do you need this data and what is the best way to receive it? Make sure you can get the data you need and in the correct format. Determine whether you can perform a full upload each time or just the changes from the previous dataset. Think about whether you want the data delivered via email, direct download or automatically to your Amazon S3 account.
- Who should have access to the data and how will it be stored once it is harvested?
- Finally, the plan should include what you are going to do with all this newly acquired data and who is receiving the final analysis.

4) Be willing to change your plan.

This one may seem counterintuitive after so much focus on having a game plan. However, remember to be flexible. The whole point of hiring experts is that they are the experts. A plan will make discussions much more productive, but the experts will probably offer insight you hadn’t thought of. Be willing to integrate their advice into your plan.

5) Have a list of questions ready for the company.

Having a list of questions ready for the data scraping company will help keep you in charge of the discussions and negotiations. Here are some points that you should know before choosing a data scraping partner:
- Can they start helping you immediately? Make sure they have the infrastructure and staff to get - you off the ground in a matter of weeks, not months.
- Make sure you can access them via email and phone. Also make sure you have access to those -actually performing the data scraping, not just a call center.
- Can they tailor their processes to fit with your requirements and organisational systems?
- Can they scrape more than plain text? Make sure they can harvest complex and dynamic sites -with JavaScript and AJAX. If a website’s content can be viewed on a browser, they should be-- able to get it for you.
- Make sure they have monitoring systems in place that can detect changes, breakdowns, and -quality issues. This will ensure you have access to a persistent and reliable flow of data, even - when the targeted websites change formats.
- As your data grows, can they easily keep up? Make sure they have scalable solutions that could - handle all that unstructured web data.
- Will they protect your company? Make sure they know discretion is important and that they will not advertise you as a client unless you give permission. Also, check to see how they disguise their scrapers so that the data harvesting cannot be traced back to your business.

6) Check their reviews.

Do a bit of your own manual data scraping to see what others business are saying about the companies you are researching.

7) Make sure the plan the company offers is cost-effective.

Here are a few questions to ask to make sure you get a full view of the costs and fees in the estimate:
- Is there a setup fee?
- What are the fixed costs associated with this project?
- What are the variable costs and how are they calculated?
- Are there any other taxes, fees or things that I could be charged for that are not listed on this -quote?
- What are the payment terms?

Source Url :-http://www.data-scraping.com.au/data-scraping-doesnt-have-to-be-hard/

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

Data Extraction/ Web Scraping Services

Making an informed business decision requires extracting, harvesting and exploiting information from diverse sources. Data extraction or web scraping (also known as web harvesting) is the process of mining information from websites using software, substantiated with human intelligence. The content 'scraped' from web sources using algorithms is stored in a structured format, so that it can be manually analyzed later.

Case in Point: How do price comparison websites acquire their pricing data? It is mostly by 'scraping' the information from online retailer websites.

We offers data extraction / web scraping services for retrieving data for advanced data processing or archiving from a variety of online sources and medium. Nonetheless, data extraction is a time consuming process, and if not conducted meticulously, it can result in loads of errors. A leading web scraping company, we can deliver required information within a short turnaround time, employing an extensive array of online sources.

Our Process Of Data Extraction/ Web Scraping, Involves:

- Capturing relevant data from the web, which is raw and unstructured
- Reviewing and refining the obtained data sets
- Formatting the data, consistent with the requirements of the client
- Organizing website and email lists, and contact details in an excel sheet
- Collating and summarizing the information, if required

Our professionals are adept at extracting data pertaining to your competition, their pricing strategy, gathering information about various product launches, their new and innovative features, etc., for enterprises, market research companies or price comparison websites through professional market research and subject matter blogs.

Our key Services in Web Scraping/ Database Extraction include:

We offer a comprehensive range of data extraction and scraping services right from Screen Scraping, Webpage / HTML Page Scraping, Semantic / Syntactic Scraping, Email Scraping to Database Extraction, PDF Data Extraction Services, etc.

- Extracting meta data from websites, blogs, and forums, etc.
- Data scraping from social media sites
- Data quarrying for online news and media sites from different online news and PR sources
- Data scraping from business directories and portals
- Data scraping pertaining to legal / medical / academic research
- Data scraping from real estate, hotels & restaurant, financial websites, etc.

Contact us to outsource your Data Scraping / Web Extraction Services or to-  learn more about our other data related services.

Source Url :-http://www.data-entry-india.com/data-extraction-web-scraping-services.html

Website Data Scraping Services

To help you in creating information databases, business portals and mailing lists, we provide efficient and accurate website data scraping services. We have been serving many worldwide clients for their specific requirements and delivering them structured data after collecting from World Wide Web. Our capabilities allow us to scrape data from an assortment of sources including websites, blogs, podcasts, and online directories etc.

 We have a team of skilled and experienced web scraping professionals who can deliver you results in the file format you needed such as Excel, CSV, Access, TXT and My SQL. We have expertise in automated as well as manual data scraping that ensure one hundred percent accuracy in the outcome. Our web data scraping professionals not only help you in gathering high-value data from the internet but also enable you to improve strategic insights and create new business opportunities.

What our website data scraping services include?

We provide a wide range of website data scraping services including data collection, data extraction, screen scraping and web data scraping. With its web scraping services, Data Outsourcing India helps you to crawl thousands of websites and gather useful information or data flawlessly. Using our web data scraping service, we can extract phone numbers, email addresses, reviews, ratings, business addresses, product details, contact information (name, title, department, company, country, city, state, etc.) and other business related data from following sources:

- Market place portals
- Auction portals
- Business directories
- Government online databases
- Statistics data from websites
- Social networking sites
- Online shopping portals
- Job portals
- Classifieds websites
- Hotels and restaurant portals
- News portals

Why outsource website data scraping services to us?

Our web data extraction experts have in-depth knowledge for screen scraping processes and it enables us to extract essential information from any online portal or database. If you outsource website data scraping to us, we assure you about accurate collection of information in easy to retrieval format. Here are some key benefits you gain with us:

- Tailor made processes to suit any kind of need
- Strict security and confidentiality policies
- A rigorous Quality Control (QC) process
- Leverage an optimum mix of techniques and technology
- Almost 60-65% savings on operational cost
- You get you project completed in industry’s best TAT
- Round-the-clock customer support
- Access to a dedicated team of website data scraping professionals

 With our quick, accurate and affordable web scraping services, we are helping worldwide large as well as medium size companies. Our clients are from different industries- including real estate, healthcare, banking, finance, insurance, automobiles, marketing, academics, human resources, ecommerce, manufacturing, travel, hotels and more. The-  multifaceted experience facilitates us in delivering every online data scraping project with ZERO error rates.

Source Url:-http://www.dataoutsourcingindia.com/website-data-scraping-services.html