Document (#27781)

Author

Guerrero Bote, V.P.
López-Pujalte, C.
Faba, C.
Reyes, M.J.
Zapica, F.
Moya-Anegón, F. de

Title

Artificial neural networks applied to information retrieval

Source

Challenges in knowledge representation and organization for the 21st century: Integration of knowledge across boundaries. Proceedings of the 7th ISKO International Conference Granada, Spain, July 10-13, 2002. Ed.: M. López-Huertas

Imprint

Würzburg : Ergon Verlag

Year

2003

Pages

S.572-577

Series

Advances in knowledge organization; vol.8

Abstract

Connectionist models or neural networksare a type of AI technique that is based an small interconnected processing nodes which yield an overall behaviour that is intelligent. They have a very broad utility. In IR, they have been used in filtering information, query expansion, relevance feedback, clustering terms or documents, the topological organization of documents, labeling groups of documents, interface design, reduction of document dimension, the classification of the terms in a brain-storming session, etc. The present work is a fairly exhaustive study and classification of the application of this type of technique to IR. For this purpose, we focus an the main publications in the area of IR and neural networks, as well as an some applications of our own design.

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3. Cortex, E.M.; Park, S.C.; Kim, S.: ¬The hybrid application of an inductive learning method and a neural network for intelligent information retrieval (1995) 0.23

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4. Malak, P.: Is the Artificial Intelligence applicable for the libraries purposes? (2005) 0.19

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5. Guerrero-Bote, V.P.; Moya Anegón, F. de; Herrero Solana, V.: Document organization using Kohonen's algorithm (2002) 0.17

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