What are the methodologies of web mining?

Web mining is the application of machine learning (data mining) approaches to web-based data for the goals of learning or deriving knowledge. Web mining methodologies can be defined into one of three distinct elements which are as follows −

Web Usage Mining − Web usage mining is a kind of web mining that enables the set of Web access data for Web pages. This usage data supports the direction leading to accessed Web pages.

This data is gathered automatically into connection logs via the Web server. CGI scripts provide useful data including referrer logs, user subscription data, and survey logs. This category is essential to the complete use of data mining for organization and their internet/ intranet-based applications and data access.

Usage mining enables companies to make productive data about the future of their business serviceability. Various data can be derived from the collective data of lifetime user value, product cross-marketing approaches, and promotional campaign effectiveness.

The usage data that is gathered provides the organization with the ability to make results more efficient for their businesses and enhancing of sales. Usage records can also be beneficial for creating marketing skills that will out-sell the competitors and enhance the company’s services or product on a larger level.

Web Structure Mining − Web structure mining is a tool that can recognize the relationship among Web pages linked by data or direct link connection. This structure information is discoverable by the arrangement of web structure schema through database approaches for Web pages.

This connection enables a search engine to pull records relating to a search query directly to the connecting Web page from the website the content rests upon. This completion takes place through the need of spiders browsing the websites, fetching the home page, then, and connecting the information through reference links to bring forth the definite page including the desired data.

The goal of structure mining is to derive previously unknown relationships among Web pages. This structure of data mining supports to use of a business to link the data of its website to allow navigation and cluster data into site maps. This enables its users the ability to access the desired data through keyword relations and content mining.

Web Content Mining − Web content mining is the browsing and mining of text, images, and graphs of a Web page to decide the relevance of the content to the search query.

This browsing is done after the clustering of web pages through structure mining and supports the results depending upon the level of relevance to the submitted query. With a large amount of data that is accessible on the World Wide Web, content mining supports the results lists to search engines in a series of largest relevance to the keywords in the query.