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@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