Improving the learning of Boolean queries by means of a multiobjective IQBE evolutionary algorithm

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{CHL:IPM:06,
  title =        "Improving the learning of {Boolean} queries by means
                 of a multiobjective IQBE evolutionary algorithm",
  author =       "O. Cordon and E. Herrera-Viedma and M. Luque",
  journal =      "Information Processing and Management",
  year =         "2006",
  volume =       "42",
  number =       "3",
  pages =        "615--632",
  month =        may,
  keywords =     "genetic algorithms, genetic programming, Boolean
                 information retrieval systems, Inductive query by
                 example, Multiobjective evolutionary algorithms, Query
                 learning",
  DOI =          "doi:10.1016/j.ipm.2005.02.006",
  abstract =     "The Inductive Query By Example (IQBE) paradigm allows
                 a system to automatically derive queries for a specific
                 Information Retrieval System (IRS). Classic IRSs based
                 on this paradigm [Smith, M., & Smith, M. (1997). The
                 use of genetic programming to build Boolean queries for
                 text retrieval through relevance feedback. Journal of
                 Information Science, 23(6), 423-431
                 \cite{MartinPSmith:1997:JIS}] generate a single
                 solution (Boolean query) in each run, that with the
                 best fitness value, which is usually based on a
                 weighted combination of the basic performance criteria,
                 precision and recall. A desirable aspect of IRSs,
                 especially of those based on the IQBE paradigm, is to
                 be able to get more than one query for the same
                 information needs, with high precision arid recall
                 values or with different trade-offs between both.

                 IQBE process is proposed combining a previous basic
                 algorithm to automatically derive Boolean queries for
                 Boolean IRSs [Smith, M., & Smith, M. (1997). The use of
                 genetic programming to build Boolean queries for text
                 retrieval through relevance feedback. Journal of
                 Information Science, 23(6), 423-431] and an advanced
                 evolutionary multiobjective approach [Coello, C. A.,
                 Van Veldhuizen, D. A., & Lamant, G. B. (2002).
                 Evolutionary algorithms for solving multiobjective
                 problems. Kluwer Academic Publishers], which obtains
                 several queries with a different precision recall
                 trade-off in a single run. The performance of the new
                 proposal will be tested on the Cranfield and CACM
                 collections and compared to the well-known Smith and
                 Smith's algorithm, showing how it improves the learning
                 of queries and thus it could better assist the user in
                 the query formulation process.",
}

Genetic Programming entries for Oscar Cordon Enrique Herrera Viedma Maria Luque Rodriguez

Citations