Research on a Hybrid Approach for Web Usage Mining
With the large number of companies using the Internet to distribute and collect information, knowledge discovery on the web or web mining has become an important research area. Basically data mining techniques are used in web mining. Web mining is extended version of data mining. Data mining is work upon Off Line whereas Web mining is work upon OnLine. In data mining data is stored in (database) data warehouse and in web mining data is stored in server database web log. The expansion of the World Wide Web (Web for short) has resulted in a large amount of data that is now in general freely available for user access. The different types of data have to be managed and organized in such a way that they can be accessed by different users efficiently. Therefore, the application of data mining techniques on the Web is now the focus of an increasing number of researchers. Several data mining methods are used to discover the hidden information in the Web. However, Web mining does not only mean applying data mining techniques to the data stored in the Web. The algorithms have to be modified such that they better suit the demands of the Web. Web mining can be divided into three areas, namely web content mining, web structure mining and web usage mining (also called web log mining).Web content mining focuses on discovery of information stored on the Internet, i.e. the various search engines. Web content mining is the process of extracting useful information from the contents of web documents. Content data is the collection of facts a web page is designed to contain. It may consist of text, images, audio, video, or structured records such as lists and tables. Application of text mining to web content has been the most widely researched. Issues addressed in text mining include topic discovery and tracking, extracting association patterns, clustering of web documents and classification of web pages. Research activities on this topic have drawn heavily on techniques developed in other disciplines such as Information Retrieval (IR) and Natural Language Processing (NLP) While there exists a significant body of work in extracting knowledge from images in the fields of image processing and computer vision, the application of these techniques to web content mining has been limited. Web structure mining can be used when improving the structural design of a website. The structure of a typical web graph consists of web pages as nodes, and hyperlinks as edges connecting related pages. Web structure mining is the process of discovering structure information from the web. This can be further divided into two kinds based on the kind of structure information used.