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  • × author_ss:"López-Pujalte, C."
  1. Guerrero Bote, V.P.; López-Pujalte, C.; Faba, C.; Reyes, M.J.; Zapica, F.; Moya-Anegón, F. de: Artificial neural networks applied to information retrieval (2003) 0.00 
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    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.
  2. López-Pujalte, C.; Guerrero-Bote, V.P.; Moya-Anegón, F. de: Genetic algorithms in relevance feedback : a second test and new contributions (2003) 0.00 
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    Source
    Information processing and management. 39(2003) no.5, S.669-687
  3. López-Pujalte, C.; Guerrero-Bote, V.P.; Moya-Anegón, F. de: Order-based fitness functions for genetic algorithms applied to relevance feedback (2003) 0.00 
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    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.2, S.152-160

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