Name: Knowledge Seeker - Ontology Modelling for Information Search and Management de Lee; Liu; Lim(Springer pg) (en Inglés)
Price: 386223.00 COP
Availability: InStock
Author: Lim Edward H. Y.,Liu James N. K.,Lee Raymond S. T.
ISBN: 9783642266911

portada Knowledge Seeker - Ontology Modelling for Information Search and Management de Lee; Liu; Lim(Springer pg) (en Inglés)

Knowledge Seeker - Ontology Modelling for Information Search and Management de Lee; Liu; Lim(Springer pg) (en Inglés)

Formato

Libro Físico

Editorial

Springer Pg

Autor

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

Idioma

Inglés

N° páginas

237

Encuadernación

Tapa Blanda

ISBN13

9783642266911

Knowledge Seeker - Ontology Modelling for Information Search and Management de Lee; Liu; Lim(Springer pg) (en Inglés)

Lim Edward H. Y.,Liu James N. K.,Lee Raymond S. T. (Autor) · Springer Pg · Tapa Blanda

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Reseña del libro "Knowledge Seeker - Ontology Modelling for Information Search and Management de Lee; Liu; Lim(Springer pg) (en Inglés)"

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.