A new evolutionary algorithm combining simulated annealing and genetic programming for relevance feedback in fuzzy information retrieval systems

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@Article{cordon:2002:SC,
  author =       "O. Cordon and F. Moya and C. Zarco",
  title =        "A new evolutionary algorithm combining simulated
                 annealing and genetic programming for relevance
                 feedback in fuzzy information retrieval systems",
  journal =      "Soft Computing - A Fusion of Foundations,
                 Methodologies and Applications",
  year =         "2002",
  volume =       "6",
  number =       "5",
  pages =        "308--319",
  month =        aug,
  keywords =     "genetic algorithms, genetic programming, Fuzzy
                 information retrieval, Relevance feedback, Evolutionary
                 algorithms, Simulated annealing",
  ISSN =         "1432-7643",
  DOI =          "doi:10.1007/s00500-002-0184-8",
  abstract =     "Relevance feedback techniques have demonstrated to be
                 a powerful means to improve the results obtained when a
                 user submits a query to an information retrieval system
                 as the world wide web search engines. These kinds of
                 techniques modify the user original query taking into
                 account the relevance judgements provided by him on the
                 retrieved documents, making it more similar to those he
                 judged as relevant. This way, the new generated query
                 permits to get new relevant documents thus improving
                 the retrieval process by increasing recall. However,
                 although powerful relevance feedback techniques have
                 been developed for the vector space information
                 retrieval model and some of them have been translated
                 to the classical Boolean model, there is a lack of
                 these tools in more advanced and powerful information
                 retrieval models such as the fuzzy one. In this
                 contribution we introduce a relevance feedback process
                 for extended Boolean (fuzzy) information retrieval
                 systems based on a hybrid evolutionary algorithm
                 combining simulated annealing and genetic programming
                 components. The performance of the proposed technique
                 will be compared with the only previous existing
                 approach to perform this task, Kraft et al.'s method,
                 showing how our proposal outperforms the latter in
                 terms of accuracy and sometimes also in time
                 consumption. Moreover, it will be showed how the
                 adaptation of the retrieval threshold by the relevance
                 feedback mechanism allows the system effectiveness to
                 be increased.",
}

Genetic Programming entries for Oscar Cordon Felix de Moya Carmen Zarco Fernandez

Citations