Web Community Directories: A New Approach to Web Personalization

摘要

This paper introduces a new approach to Web Personaliza-tion, named Web Community Directories that aims to tackle the prob-lem of information overload on the WWW. This is realized by applying personalization techniques to the well-known concept of Web Directories. The Web directory is viewed as a concept hierarchy which is generated by a content-based document clustering method. Personalization is realized by constructing community models on the basis of usage data collected by the proxy servers of an Internet Service Provider. For the construction of the community models, a new data mining algorithm, called Community Directory Miner, is used. This is a simple cluster mining algorithm which has been extended to ascend a concept hierarchy, and specialize it to the needs of user communities. The data that are mined present a number of peculiarities such as their large volume and semantic diversity. Initial results presented in this paper illustrate the use of the methodology and provide an indication of the behavior of the new mining method.