Knowledge Seeker Ontology Modelling for Information Search and Management: A Compendium - Couverture rigide
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Synopsis
The Knowledge Seeker is a useful system to develop various intelligent applications such as ontology-based search engine, ontology-based text classification system, ontological agent system, and semantic web system etc. The Knowledge Seeker contains four different ontological components. First, it defines the knowledge representation model ¡V Ontology Graph. Second, an ontology learning process that based on chi-square statistics is proposed for automatic learning an Ontology Graph from texts for different domains. Third, it defines an ontology generation method that transforms the learning outcome to the Ontology Graph format for machine processing and also can be visualized for human validation. Fourth, it defines different ontological operations (such as similarity measurement and text classification) that can be carried out with the use of generated Ontology Graphs. The final goal of the KnowledgeSeeker system framework is that it can improve the traditional information system with higher efficiency. In particular, it can increase the accuracy of a text classification system, and also enhance the search intelligence in a search engine. This can be done by enhancing the system with machine processable ontology.
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Présentation de l'éditeur
This detailed survey of the ontology modelling application Knowledge Seeker demonstrates how it can improve the efficiency of traditional information systems, increase the accuracy of text classification, and enhance the capabilities of search engines.
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Knowledge Seeker - Ontology Modelling for Information Search and Management (eng)
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Etat : new. Questo è un articolo print on demand. N° de réf. du vendeur 3d374e045d10bfdcd9dd5d89b2ecdfc4
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Knowledge Seeker - Ontology Modelling for Information Search and Management
Edité par
Springer Berlin Heidelberg, Springer Berlin Heidelberg Jan 2011, 2011
ISBN 10 : 3642179150
ISBN 13 : 9783642179150
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The Knowledge Seeker is a useful system to develop various intelligent applications such as ontology-based search engine, ontology-based text classification system, ontological agent system, and semantic web system etc. The Knowledge Seeker contains four different ontological components. First, it defines the knowledge representation model ¡V Ontology Graph. Second, an ontology learning process that based on chi-square statistics is proposed for automatic learning an Ontology Graph from texts for different domains. Third, it defines an ontology generation method that transforms the learning outcome to the Ontology Graph format for machine processing and also can be visualized for human validation. Fourth, it defines different ontological operations (such as similarity measurement and text classification) that can be carried out with the use of generated Ontology Graphs. The final goal of the KnowledgeSeeker system framework is that it can improve the traditional information system with higher efficiency. In particular, it can increase the accuracy of a text classification system, and also enhance the search intelligence in a search engine. This can be done by enhancing the system with machine processable ontology. The KnowledgeSeeker is a useful system to develop various intelligent applications such as ontology-based search engine, ontology-based text classification system, ontological agent system, and semantic web system etc. The KnowledgeSeeker contains four different ontological components. First, it defines the knowledge representation model ¡V Ontology Graph. Second, an ontology learning process that based on chi-square statistics is proposed for automatic learning an Ontology Graph from texts for different domains. Third, it defines an ontology generation method that transforms the learning outcome to the Ontology Graph format for machine processing and also can be visualized for human validation. Fourth, it defines different ontological operations (such as similarity measurement and text classification) that can be carried out with the use of generated Ontology Graphs. The final goal of the KnowledgeSeeker system framework is that it can improve the traditional information system with higher efficiency. In particular, it can increase the accuracy of a text classification system, and also enhance the search intelligence in a search engine. This can be done by enhancing the system with machine processable ontology. 264 pp. Englisch. N° de réf. du vendeur 9783642179150
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Knowledge Seeker - Ontology Modelling for Information Search and Management: A Compendium
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Knowledge Seeker - Ontology Modelling for Information Search and Management
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Springer Berlin Heidelberg, 2011
ISBN 10 : 3642179150
ISBN 13 : 9783642179150
Neuf
Couverture rigide
Vendeur : moluna, Greven, Allemagne
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Knowledge Seeker - Ontology Modelling for Information Search and Management
Edité par
Springer, Springer Berlin Heidelberg Jan 2011, 2011
ISBN 10 : 3642179150
ISBN 13 : 9783642179150
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The Knowledge Seeker is a useful system to develop various intelligent applications such as ontology-based search engine, ontology-based text classification system, ontological agent system, and semantic web system etc. The Knowledge Seeker contains four different ontological components. First, it defines the knowledge representation model ¡V Ontology Graph. Second, an ontology learning process that based on chi-square statistics is proposed for automatic learning an Ontology Graph from texts for different domains. Third, it defines an ontology generation method that transforms the learning outcome to the Ontology Graph format for machine processing and also can be visualized for human validation. Fourth, it defines different ontological operations (such as similarity measurement and text classification) that can be carried out with the use of generated Ontology Graphs. The final goal of the KnowledgeSeeker system framework is that it can improve the traditional information system with higher efficiency. In particular, it can increase the accuracy of a text classification system, and also enhance the search intelligence in a search engine. This can be done by enhancing the system with machine processable ontology.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 264 pp. Englisch. N° de réf. du vendeur 9783642179150
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Knowledge Seeker - Ontology Modelling for Information Search and Management: A Compendium (Intelligent Systems Reference Library)
Vendeur : Revaluation Books, Exeter, Royaume-Uni
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Hardcover. Etat : Brand New. 264 pages. 9.25x6.25x0.75 inches. In Stock. N° de réf. du vendeur x-3642179150
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Knowledge Seeker - Ontology Modelling for Information Search and Management : A Compendium
Edité par
Springer Spektrum, 2011
ISBN 10 : 3642179150
ISBN 13 : 9783642179150
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The Knowledge Seeker is a useful system to develop various intelligent applications such as ontology-based search engine, ontology-based text classification system, ontological agent system, and semantic web system etc. The Knowledge Seeker contains four different ontological components. First, it defines the knowledge representation model ¡V Ontology Graph. Second, an ontology learning process that based on chi-square statistics is proposed for automatic learning an Ontology Graph from texts for different domains. Third, it defines an ontology generation method that transforms the learning outcome to the Ontology Graph format for machine processing and also can be visualized for human validation. Fourth, it defines different ontological operations (such as similarity measurement and text classification) that can be carried out with the use of generated Ontology Graphs. The final goal of the KnowledgeSeeker system framework is that it can improve the traditional information system with higher efficiency. In particular, it can increase the accuracy of a text classification system, and also enhance the search intelligence in a search engine. This can be done by enhancing the system with machine processable ontology. The KnowledgeSeeker is a useful system to develop various intelligent applications such as ontology-based search engine, ontology-based text classification system, ontological agent system, and semantic web system etc. The KnowledgeSeeker contains four different ontological components. First, it defines the knowledge representation model ¡V Ontology Graph. Second, an ontology learning process that based on chi-square statistics is proposed for automatic learning an Ontology Graph from texts for different domains. Third, it defines an ontology generation method that transforms the learning outcome to the Ontology Graph format for machine processing and also can be visualized for human validation. Fourth, it defines different ontological operations (such as similarity measurement and text classification) that can be carried out with the use of generated Ontology Graphs. The final goal of the KnowledgeSeeker system framework is that it can improve the traditional information system with higher efficiency. In particular, it can increase the accuracy of a text classification system, and also enhance the search intelligence in a search engine. This can be done by enhancing the system with machine processable ontology. N° de réf. du vendeur 9783642179150
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Knowledge Seeker - Ontology Modelling for Information Search and Management : A Compendium
Edité par
J.B. Metzler, 2011
ISBN 10 : 3642179150
ISBN 13 : 9783642179150
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Couverture rigide
Vendeur : Buchpark, Trebbin, Allemagne
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Etat : Sehr gut. Zustand: Sehr gut | Seiten: 264 | Sprache: Englisch | Produktart: Bücher | The Knowledge Seeker is a useful system to develop various intelligent applications such as ontology-based search engine, ontology-based text classification system, ontological agent system, and semantic web system etc. The Knowledge Seeker contains four different ontological components. First, it defines the knowledge representation model ¡V Ontology Graph. Second, an ontology learning process that based on chi-square statistics is proposed for automatic learning an Ontology Graph from texts for different domains. Third, it defines an ontology generation method that transforms the learning outcome to the Ontology Graph format for machine processing and also can be visualized for human validation. Fourth, it defines different ontological operations (such as similarity measurement and text classification) that can be carried out with the use of generated Ontology Graphs. The final goal of the KnowledgeSeeker system framework is that it can improve the traditional information system with higher efficiency. In particular, it can increase the accuracy of a text classification system, and also enhance the search intelligence in a search engine. This can be done by enhancing the system with machine processable ontology. N° de réf. du vendeur 10043869/2
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Knowledge Seeker - Ontology Modelling for Information Search and Management Liu, James N. K.
Edité par
J.B. Metzler, 2011
ISBN 10 : 3642179150
ISBN 13 : 9783642179150
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Couverture rigide
Vendeur : BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, Allemagne
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Hardcover. Etat : gut. 2011. Knowledge Seeker - Ontology Modelling for Information Search and Management In deutscher Sprache. pages. N° de réf. du vendeur BN176089
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