Subjectively Related Association Term Discovery towards Personalized Web Information Retrieval

  • Authors:
  • Seung Yeol Yoo

  • Affiliations:
  • -

  • Venue:
  • WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
  • Year:
  • 2008

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Abstract

In this paper, we propose a new semi-supervised clustering methodology to extract topically coherent contents from given Web pages, according to a user's topic interests. It is an effort to resolve low information retrieval performance, caused by one fact that even a single Web page often contains multi-topic related contents. Our evaluation results showed some advantages of our semi-supervised clustering methodology: it reduces the needs of term classification knowledge between the given Web pages and a user's topic interests. It also gets better clustering performances than those which can be achieved with the well-known supervised feature-term selection method $\chi^{2}$ statistics.