An analysis of the Solution Space for Genetically Programmed Term-Weighting Schemes in Information Retrieval

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{Cummins:2006:AICS,

• author = "Ronan Cummins and Colm O'Riordan",
• title = "An analysis of the Solution Space for Genetically Programmed Term-Weighting Schemes in Information Retrieval",
• booktitle = "17th Irish Artificial Intelligence and Cognitive Science Conference (AICS 2006)",
• year = "2006",
• editor = "D. A. Bell",
• address = "Queen's University, Belfast",
• month = "11th-13th " # sep,
• organisation = "Artificial Intelligence Association of Ireland",
• keywords = "genetic algorithms, genetic programming",
• URL = "http://ir.dcs.gla.ac.uk/~ronanc/papers/cumminsAICS06.pdf",
• size = "10 pages",
• abstract = "Evolutionary algorithms and Genetic Programming (GP) in particular are increasingly being applied to the problem of evolving term-weighting schemes in Information Retrieval (IR). One fundamental problem with the solutions generated by this stochastic, non-deterministic process is that they are often difficult to analyse. We develop a number of 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. Using this framework we show that our evolved solutions lie in a different part of the solution space than two of the best benchmark term-weighting schemes available.",
• notes = "http://www.cs.qub.ac.uk/aics06/aics.html",

}

Genetic Programming entries for Ronan Cummins Colm O'Riordan

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