Web usage mining is the type of Web mining activity that involves the automatic discovery of user access patterns from one or more Web servers. As more organizations rely on the Internet and the World Wide Web to conduct business, the traditional strategies and techniques for market analysis need to be revisited in this context. Organizations often generate and collect large volumes of data in their daily operations. Most of this information is usually generated automatically by Web servers and collected in server access logs. Other sources of user information include referrer logs which contains information about the referring pages for each page reference, and user registration or survey data gathered via tools such as CGI scripts.
Analyzing such data can help these organizations to determine the life time value of customers, cross marketing strategies across products, and effectiveness of promotional campaigns, among other things. Analysis of server access logs and user registration data can also provide valuable information on how to better structure a Web site in order to create a more effective presence for the organization. In organizations using intranet technologies, such analysis can shed light on more effective management of workgroup communication and organizational infrastructure. Finally, for organizations that sell advertising on the World Wide Web, analyzing user access patterns helps in targeting ads to specific groups of users.
Most of the existing Web analysis tools [Inc96,eSI95,net96] provide mechanisms for reporting user activity in the servers and various forms of data filtering. Using such tools, for example, it is possible to determine the number of accesses to the server and the individual files within the organization's Web space, the times or time intervals of visits, and domain names and the URLs of users of the Web server. However, in general, these tools are designed to deal handle low to moderate traffic servers, and furthermore, they usually provide little or no analysis of data relationships among the accessed files and directories within the Web space.
More sophisticated systems and techniques for discovery and analysis of patterns are now emerging. These tools can be placed into two main categories, as discussed below.
