Knowledge Discovery Framework for Community Web Directories

In contrast to most of the work on Web usage mining, the usage data that are analyzed here correspond to user navigation throughout the Web, rather than a particular Web site, exhibiting as a result a high degree of thematic diversity. For modeling the user communities, we introduce a novel methodology that combines the user's browsing behavior with thematic information from the Web directories. The proposed personalization methodology is evaluated in a general-purpose Web directory, indicating its potential value to the web user. A Web directory, such as Yahoo (www.yahoo.com) and the Open Directory project (ODP) (dmoz.org), allows users to find Web sites related to the topic they are interested in, starting with broad categories and gradually narrowing down, choosing the category most related to their interests. For personalization Web directories uses the OCDM, OPDM &OCPDM algorithms. The experiment results show the effectiveness of the different machine learning techniques on the task.