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

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@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

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