Grow up precision recall relationship curve in IR system using GP and fuzzy optimization in optimizing the user query

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dc.contributor.author Owais, Suhail S. J.
dc.contributor.author Snášel, Václav
dc.contributor.author Krömer, Pavel
dc.date.accessioned 2007-10-10T13:27:22Z
dc.date.available 2007-10-10T13:27:22Z
dc.date.issued 2007
dc.identifier.citation Neural network world : international journal on neural and mass-parallel computing and information systems. 2007, vol. 17, issue 4, p. 295-309. en
dc.identifier.issn 1210-0552
dc.identifier.uri http://hdl.handle.net/10084/63505
dc.language.iso en en
dc.publisher Akademie věd České republiky, Ústav informatiky en
dc.relation.ispartofseries Neural network world : international journal on neural and mass-parallel computing and information systems en
dc.subject information retrieval en
dc.subject genetic programming en
dc.subject fuzzy optimization en
dc.subject Boolean operator en
dc.subject term weights en
dc.subject precision en
dc.subject recall and harmonic mean en
dc.title Grow up precision recall relationship curve in IR system using GP and fuzzy optimization in optimizing the user query en
dc.type Article en
dc.identifier.location Není ve fondu ÚK en
dc.description.abstract-en An information retrieval (IR) system (IRs) (search engine) is said to be efficient, to the degree that always evaluates each object in the information base (database, document base, web,...) like the expert. The ability of IRs's is to retrieve mostly all relevant objects (measured by the recall), and only the (most) relevant objects (measured by the precision) from the collection queried. Recall and precision measures provide the classical measure of the retrieval efficiency. They measure the degree to which the query answer (the set of documents that retrieved by IRs as response to the user query). Where, the query answer is the set of relevant documents in the information based queried. Retrieving most relevant documents to the user query in IRs was one of the most important methods of World Wide Web (WWW) search engines used in the world now. So the searchers aim to use genetic programming (GP) and fuzzy optimization to optimize the user search query in the Boolean IRs model and in the fuzzy IRs model; and to use more Boolean operators (AND, OR, XOR, OF, and NOT) instead of using the standard operators (AND, OR, and NOT), and to use weights for terms and for Boolean operators. Weights are used to give the users more relaxation in defining how much the importance of the terms and of the Boolean operators is. The terms and the Boolean operators' weights are used in fuzzy IRs model. In addition, it investigates extensions of the classical measurement of effectiveness in IRs, precision; recall and harmonic mean. The researchers use harmonic mean measure as an objective function which uses both measures precision and recall at once for evaluating the results of the two IRs models to grow up the precision-recall relationship curve. en
dc.identifier.wos 000249076100004

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