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Genetic algorithms in relevance feedback: A second test and new contributions. (English) Zbl 1055.68087

Summary: The present work is the continuation of an earlier study which reviewed the literature on relevance feedback genetic techniques that follow the vector space model (the model that is most commonly used in this type of application), and implemented them so that they could be compared with each other as well as with one of the best traditional methods of relevance feedback – the Ide dec-hi method. We here carry out the comparisons on more test collections (Cranfield, CISI, Medline, and NPL), using the residual collection method for their evaluation as is recommended in this type of technique. We also add some fitness functions of our own design.

MSC:

68T05 Learning and adaptive systems in artificial intelligence
68W05 Nonnumerical algorithms
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