Relevance Feature Discovery is an innovative model that classifies terms into distinct categories and effectively updates term weights and distribution in patterns, hence boosting text mining performance.The terms that appear more frequently in relevant papers are regarded as positive specific terms. The terms that appear more frequently in irrelevant papers are classified as negative specific terms. The goal of Relevance Feature Discovery is to extract high-quality features that accurately represent the user's demands. This system outperforms term and pattern-based techniques.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Relevance Feature Discovery is an innovative model that classifies terms into distinct categories and effectively updates term weights and distribution in patterns, hence boosting text mining performance.The terms that appear more frequently in relevant pap. Codice articolo 1590607281
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Relevance Feature Discovery is an innovative model that classifies terms into distinct categories and effectively updates term weights and distribution in patterns, hence boosting text mining performance.The terms that appear more frequently in relevant papers are regarded as positive specific terms. The terms that appear more frequently in irrelevant papers are classified as negative specific terms. The goal of Relevance Feature Discovery is to extract high-quality features that accurately represent the user's demands. This system outperforms term and pattern-based techniques.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch. Codice articolo 9786207474745
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Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Relevance Feature Discovery is an innovative model that classifies terms into distinct categories and effectively updates term weights and distribution in patterns, hence boosting text mining performance.The terms that appear more frequently in relevant papers are regarded as positive specific terms. The terms that appear more frequently in irrelevant papers are classified as negative specific terms. The goal of Relevance Feature Discovery is to extract high-quality features that accurately represent the user's demands. This system outperforms term and pattern-based techniques. Codice articolo 9786207474745
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Da: preigu, Osnabrück, Germania
Taschenbuch. Condizione: Neu. Relevance Feature Search for Text Mining | Novel approach for Text Mining | Rekha Kamble (u. a.) | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786207474745 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Codice articolo 128971791
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