Document (#27758)

Author
Lopez-Pujalte, C.
Guerrero Bote, V.P.
Moya-Anegón, F. de
Title
Evaluation of the application of genetic algorithms to relevance feedback
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.422-428
Series
Advances in knowledge organization; vol.8
Abstract
We evaluated the different genetic algorithms applied to relevance feedback that are to be found in the literature and which follow the vector space model (the most commonly used model in this type of application). They were compared with a traditional relevance feedback algorithm - the Ide dec-hi method - since this had given the best results in the study of Salton & Buckley (1990) an this subject. The experiment was performed an the Cranfield collection, and the different algorithms were evaluated using the residual collection method (one of the most suitable methods for evaluating relevance feedback techniques). The results varied greatly depending an the fitness function that was used, from no improvement in some of the genetic algorithms, to a more than 127% improvement with one algorithm, surpassing even the traditional Ide dec-hi method. One can therefore conclude that genetic algorithms show great promise as an aid to implementing a truly effective information retrieval system.
Theme
Retrievalalgorithmen

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  4. Smith, M.P.; Smith, M.: ¬The use of genetic programming to build Boolean queries for text retrieval through relevance feedback (1997) 0.43
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