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Neural navigation interfaces for Information Retrieval: Are they more than an appealing idea?

Neural navigation interfaces for Information Retrieval: Are they more than an appealing idea? Neural networks have recently been proposed for the construction of navigation interfaces for Information Retrieval systems. In this paper, we give an overview of some current research in this area. Most of the cited approaches use (variants) of the well-known Kohonen network. The Kohonen network implements a topology-preserving dimensionality-reducing mapping, which can be applied for information visualization. We identify a number of problems in the application of Kohonen networks for Information Retrieval, most notably scalability, reliability and retrieval effectiveness. To solve these problems we propose to use the Growing Cell Structures network, a variant of the Kohonen network which shows a more flexible adaptation to the domain structure. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Artificial Intelligence Review Springer Journals

Neural navigation interfaces for Information Retrieval: Are they more than an appealing idea?

Artificial Intelligence Review , Volume 10 (6) – May 31, 2004

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References (29)

Publisher
Springer Journals
Copyright
Copyright
Subject
Computer Science; Artificial Intelligence; Computer Science, general
ISSN
0269-2821
eISSN
1573-7462
DOI
10.1007/BF00130695
Publisher site
See Article on Publisher Site

Abstract

Neural networks have recently been proposed for the construction of navigation interfaces for Information Retrieval systems. In this paper, we give an overview of some current research in this area. Most of the cited approaches use (variants) of the well-known Kohonen network. The Kohonen network implements a topology-preserving dimensionality-reducing mapping, which can be applied for information visualization. We identify a number of problems in the application of Kohonen networks for Information Retrieval, most notably scalability, reliability and retrieval effectiveness. To solve these problems we propose to use the Growing Cell Structures network, a variant of the Kohonen network which shows a more flexible adaptation to the domain structure.

Journal

Artificial Intelligence ReviewSpringer Journals

Published: May 31, 2004

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