Document (#27782)

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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