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Proceedings Paper

Effects of a dynamic word network on information retrieval
Author(s): Toshiaki Iwadera; Haruo Kimoto
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Paper Abstract

This paper describes a method of learning a user's field of interest and the effects of applying this method to information retrieval. This method uses a dynamic word network (DWN) within the framework of an associated information retrieval approach. The associated information retrieval approach aims at retrieving easily, and precisely the information that a user needs out of a database. To do this, the information retrieval system must understand what the user intends to retrieve, that is, the user's interest. An associated information retrieval system (AIRS) that incorporates this approach is now being developed. AIRS learns the user's interest from sample documents and represents the user model as a DWN. A DWN consists of nodes and links. Each node corresponds to a term which AIRS can use for retrieval and each link corresponds to the relationship between two terms. Each node also has a node weight. To evaluate DWN performance, we retrieved information using AIRS comparing the output with conventional methods. The results show how the DWN improves the precision of information retrieval.

Paper Details

Date Published: 1 July 1992
PDF: 9 pages
Proc. SPIE 1710, Science of Artificial Neural Networks, (1 July 1992); doi: 10.1117/12.140145
Show Author Affiliations
Toshiaki Iwadera, NTT Network Information Systems Labs. (Japan)
Haruo Kimoto, NTT Network Information Systems Labs. (Japan)


Published in SPIE Proceedings Vol. 1710:
Science of Artificial Neural Networks
Dennis W. Ruck, Editor(s)

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