Web mining

Web mining - is the application of data mining techniques to discover patterns from the World Wide Web. Web mining can be divided into three different types – Web usage mining, Web content mining and Web structure mining.

Web Usage Mining is the application of data mining techniques to discover interesting usage patterns from Web data in order to understand and better serve the needs of Web-based applications. Usage data captures the identity or origin of Web users along with their browsing behavior at a Web site.
Web usage mining itself can be classified further depending on the kind of usage data considered:

Studies related to work [Weichbroth et al.] are concerned with two areas: constraint-based data mining algorithms applied in Web Usage Mining and developed software tools (systems). Costa and Seco demonstrated that web log mining can be used to extract semantic information (hyponymy relationships in particular) about the user and a given community.

Web usage mining essentially has many advantages which makes this technology attractive to corporations including the government agencies. This technology has enabled e-commerce to do personalized marketing, which eventually results in higher trade volumes. Government agencies are using this technology to classify threats and fight against terrorism. The predicting capability of mining applications can benefit society by identifying criminal activities. Companies can establish better customer relationship by understanding the needs of the customer better and reacting to customer needs faster. Companies can find, attract and retain customers; they can save on production costs by utilizing the acquired insight of customer requirements. They can increase profitability by target pricing based on the profiles created. They can even find customers who might default to a competitor the company will try to retain the customer by providing promotional offers to the specific customer, thus reducing the risk of losing a customer or customers.

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