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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Knowledge Seeker - Ontology Modelling for Information Search and Management: A Compendium

Knowledge Seeker - Ontology Modelling for Information Search and Management: A Compendium

Lee, Raymond S. T.
Lim, Edward H. Y.
Liu, James N. K.

Paperback

Series: Intelligent Systems Reference Library, Book 8

Business GeneralTechnology & EngineeringGeneral Computers

ISBN10: 3642266916
ISBN13: 9783642266911
Publisher: Springer
Published: Feb 27 2013
Pages: 237
Weight: 0.82
Height: 0.55 Width: 6.14 Depth: 9.21
Language: English
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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