There is a lot of data in web documents and services. This means that the application of data mining techniques on these can help one discover useful information. It can help a business discover meaningful insights to understand its customers, products, and operations better. The business owners can then take the necessary measures to make corrections and improvements where necessary. This is good for the smooth running and growth of any business.
In this article, we will be discussing Web Mining in Business Intelligence in detail. This will let you know how to use web mining for the benefit of your business.
Table Of Contents
What is Web Mining in Business Intelligence?
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Web mining refers to the process of using data mining algorithms and techniques to extract information from the web. The information is obtained from web content, services, server logs, and hyperlinks.
Its goal is to identify patterns in web data by collecting and analyzing information to gain insights into users, trends, and the industry in general.
The content of data used for Web Mining in Business Intelligence can be a collection of facts contained on web pages, and it can consist of text, structured data like tables and lists, and even audio, image, and video. There are different sources of data during web mining, and your target source will determine the method that you will use to collect the data.
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Web Mining in Business Intelligence Techniques
There are three web mining techniques used for business intelligence:
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Web Content Mining
Web content mining refers to the process of extracting useful information from web documents. Web content consists of data in image, text, audio, and video formats. The content data are the facts contained on a web page. It can help to establish interesting patterns about the needs of users.
In this Web Mining in Business Intelligence technique, every web page is considered an individual document. Structured data is collected from unstructured websites. Web content mining facilitates data aggregation across different websites using the extracted structured data. This web mining in business intelligence technique can also be used to differentiate topics on the web.
Web Structure Mining
This Web Mining in Business Intelligence technique involves the discovery of structured information on the web. In web structure mining, the web is considered a directed graph, where the web pages are the vertices and are associated with hyperlinks.
Google applies this technique to estimate the ranking of search results based on the PageRank algorithm. The relevancy of a page is determined by how frequently it is connected to the highly related pages.
Web Usage Mining
This technique is used to extract useful data, knowledge, and information from weblog records, and it helps to determine the user access patterns for web pages. Such information can help you to identify user behaviors better. This information is collected from logs, hence, this Web Mining in Business Intelligence technique is also known as log mining.
Importance of Web Mining in Business Intelligence
Web mining can be a great source of business intelligence to understand customers, drive sales, create new opportunities, and meet mission goals. Here are some of the ways through whichWeb Mining in Business Intelligence can be helpful to a company or business:
Know your Customers Better
Web mining can help you to discover your customers’ key initiatives and their financial situation. It can also help you know what the CEO of your customer’s company is saying, as well as what your customers are saying and posting on online platforms.
Learn More about your competitors
Staying ahead of competitors is key to the survival of any business. Thus, knowing your competitors better is important. With Web Mining in Business Intelligence, you can know what your competitors are doing, what they are selling, and whether they are doing anything new or unique.
Find New Customers
Web mining can keep you updated about what is happening in the world, and let you know the best places to target your sales and reach new customers.
Monitor People’s Sentiments about your Business
By knowing what people are saying about your business, you can identify potential customer-related issues and take the appropriate action to counter them before going viral. You can also track the effectiveness of your marketing campaigns.
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Data Sources for Web Mining
The first step in web mining is to identify the data that you need to target.
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There are different sources of data for Web Mining in Business Intelligence. These include:
- Curated public sources such as Wikipedia, Wiktionary, and Wikidata.
- Social media platforms such as Facebook, Instagram, Twitter, and LinkedIn.
- Government data, for example, data.gov and United States Code.
- Company content- you can create a web crawler for your business website.
- Niche websites- like GitHub, Stack Exchange, and others.
- The World Wide Web- you can use a crawler to extract data from web pages. You can identify the web pages using search engines, for example, Bing and Google. You can then use a web crawler to extract data from the identified web pages.
- Third-party aggregators- Some websites provide free data. Such websites provide APIs for searching, filtering, and downloading content. They have data such as news stories, annual reports, company reports, worldwide patents, financial filings, and more.
- Coding- It provides a good starting point for content analysis.
- Medical and health- You can get health data from websites like Medline, MESH, CPT, and ICD codes.
Conclusion
In this article, you learned that Web mining is the technique of extracting useful information from the web. The information is extracted from web content, services, server logs, and hyperlinks. The goal of Web Mining in Business Intelligence is to identify patterns in web data to gain insights into users, trends, and the industry in general.
The three techniques used for web mining include web content mining, web structure mining, and web usage mining. The first step in web mining is to determine the source of data to the target. The target source will determine the web mining method to be used. Some of the common data sources for web mining include the world wide web, curated public sources, niche websites, social media, and more.
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