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  • × author_ss:"Smith, M.P."
  • × year_i:[1990 TO 2000}
  1. Smith, M.; Smith, M.P.; Wade, S.J.: Applying genetic programming to the problem of term weight algorithms (1995) 0.04 
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    Abstract
    Presents the results of an initial study on the application of Genetic Programming (GP) to the production of term weighting algorithms in relevance feedback systems within information retrieval systems. Compares Porter, wpq and GP algorithms with user rankings. Offers a backgroud to term weighting alsgorithms and Genetic Programming
  2. Smith, M.P.; Smith, M.: ¬The use of genetic programming to build Boolean queries for text retrieval through relevance feedback (1997) 0.03 
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    Abstract
    Reports preliminary work on the use of evolutionary computing techniques to improve Boolean information retrieval system performance through relevance feedback, such as neural networks and genetic algorithms. One specific form of genetic algorithm technique was used: that of genetic programming. Terms from relevant documents are used to create randomly Boolean queries. Boolean queires are thought of as genetic programming organisms and, as such, are used for breeding to produce new organisms. Organisms which perform well, in terms of how good they are at retrieval, are given a better chance of being selected for breeding, with the result being that the overall fitness of the organisms improve to some extent. The aim is to develop the best Boolean query for an information need, given a small corpus of test documents, and then to use that query on the full collection to retrieve yet more relevant documents
  3. Smith, M.P.; Pollitt, A.S.: ¬The potential for incorporating document ranking in the MenUSE front-end search internemdiary system (1996) 0.00 
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    Source
    Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon

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