Evolved term-weighting schemes in Information Retrieval: an analysis of the solution space

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

@Article{cummins:2007:AIR,
  author =       "Ronan Cummins and Colm O'Riordan",
  title =        "Evolved term-weighting schemes in Information
                 Retrieval: an analysis of the solution space",
  journal =      "Artificial Intelligence Review",
  year =         "2006",
  volume =       "26",
  number =       "1-2",
  pages =        "35--47",
  month =        oct,
  keywords =     "genetic algorithms, genetic programming, Information
                 Retrieval, Term-weighting schemes",
  DOI =          "doi:10.1007/s10462-007-9034-5",
  abstract =     "Evolutionary computation techniques are increasingly
                 being applied to problems within Information Retrieval
                 (IR). Genetic programming (GP) has previously been used
                 with some success to evolve term-weighting schemes in
                 IR. However, one fundamental problem with the solutions
                 generated by this stochastic, non-deterministic
                 process, is that they are often difficult to analyse.
                 In this paper, we introduce two different distance
                 measures between the phenotypes (ranked lists) of the
                 solutions (term-weighting schemes) returned by a GP
                 process. Using these distance measures, we develop
                 trees which show how different solutions are clustered
                 in the solution space. We show, using this framework,
                 that our evolved solutions lie in a different part of
                 the solution space than two of the best benchmark
                 term-weighting schemes available.",
  notes =        "Published online: 12 September 2007",
}

Genetic Programming entries for Ronan Cummins Colm O'Riordan

Citations