A Framework for the study of Evolved Term-Weighting Schemes in Information Retrieval

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

@InProceedings{rc-tir06,
  author =       "Ronan Cummins and Colm O'Riordan",
  title =        "A Framework for the study of Evolved Term-Weighting
                 Schemes in Information Retrieval",
  booktitle =    "TIR-06 Text based Information Retrieval, Workshop.
                 ECAI 2006",
  year =         "2006",
  editor =       "Benno Stein and Odej Kao",
  address =      "Riva del Garda, Italy",
  month =        "29 " # aug,
  keywords =     "genetic algorithms, genetic programming, information
                 retrieval, phenotype distance",
  URL =          "http://ww2.it.nuigalway.ie/cirg/localpubs/CumminsECAI2006-Workshop.pdf",
  URL =          "http://www-ai.upb.de/aisearch/tir-06/proceedings/cummins06-framework-for-the-study-evolved-term-weighting-schemes-IR.pdf",
  abstract =     "Evolutionary algorithms and, in particular, Genetic
                 Programming (GP) are increasingly being applied to the
                 problem of evolving term-weighting schemes in
                 Information Retrieval (IR). One fundamental problem
                 with the solutions generated by these stochastic
                 processes is that they are often difficult to analyse.
                 A number of questions regarding these evolved
                 term-weighting schemes remain unanswered. One
                 interesting question is; do different runs of the GP
                 process bring us to similar points in the solution
                 space?

                 This paper deals with determining a number of measures
                 of the distance between the ranked lists (phenotype)
                 returned by different term-weighting schemes. Using
                 these distance measures, we develop trees that show the
                 phenotypic distance between these termweighting
                 schemes. This framework gives us a representation of
                 where these evolved solutions lie in the solution
                 space.

                 Finally, we evolve several global term-weighting
                 schemes and show that this framework is indeed useful
                 for determining the relative closeness of these schemes
                 and for determining the expected performance on general
                 test data.",
  notes =        "TIR-06 http://www.aisearch.de/tir-06/",
}

Genetic Programming entries for Ronan Cummins Colm O'Riordan

Citations