Topic-based Intelligent Support System for Information Retrieval
Yasufumi Takama and Kaoru Hirota
Interdisciplinary Graduate School of Science and Engineering Tokyo Institute of Technology, Yokohama
We propose a new concept of intelligent support systems for topic-based information retrieval. As information retrieval (IR) on the World Wide Web (WWW) becomes widespread, new types of tools and systems that do not only find specific pages the user wants, but also and helping the user learn about a particular field of interest are increasingly needed. Two systems based on this consideration are introduced in this paper. One is the Fish View system for supporting document-ordering. It focuses on the user’s document-ordering (making diagrams) while reading, and the user’s viewpoint is represented by a combination of a small number of concepts taken from the existing concept structure dictionary. The extracted viewpoint can be used for measuring the similarity among documents, using fisheye matching, the extended Vector Space Model. The other is the query network for visualization of the topic distribution through WWW IR, and its concept employing the Immune Network model is introduced with preliminary experiments.