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Original Essays | September 18, 2014

Lin Enger: IMG Knowing vs. Knowing



On a hot July evening years ago, my Toyota Tercel overheated on a flat stretch of highway north of Cedar Rapids, Iowa. A steam geyser shot up from... Continue »
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Other titles in the Intelligent Systems Reference Library series:

Intelligent Systems Reference Library #8: Knowledge Seeker - Ontology Modelling for Information Search and Management: A Compendium

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Intelligent Systems Reference Library #8: Knowledge Seeker - Ontology Modelling for Information Search and Management: A Compendium Cover

 

Synopses & Reviews

Publisher Comments:

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.

Synopsis:

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.

Table of Contents

Part I Introduction.- Part II KnowledgeSeeker - An Ontology Modeling and Learning Framework.- Part III KnowledgeSeeker Applications.

Product Details

ISBN:
9783642179150
Author:
Lim, Edward H. Y.
Publisher:
Springer
Author:
Lee, Raymond S. T.
Author:
Liu, James N. K.
Subject:
Engineering - General
Subject:
Computational intelligence
Subject:
KnowledgeSEEKER
Subject:
ontology learning
Subject:
ontology modelling
Subject:
Artificial Intelligence (incl. Robotics)
Subject:
Operations Research/Decision Theory
Subject:
Operations Research/Decision Theory <p>Well structured presentation of Knowledge Seeker – an Ontology Modelling and Learning Framework</p><p>Compendium of Ontology Modelling for Information Search and Management</p>Written by leading experts in this fie
Subject:
Engineering-General Engineering
Subject:
Computers-Reference - General
Subject:
Artificial Intelligence
Subject:
Operation Research/Decision Theory
Copyright:
Edition Description:
2011
Series:
Intelligent Systems Reference Library
Series Volume:
8
Publication Date:
20110319
Binding:
HARDCOVER
Language:
English
Pages:
263
Dimensions:
235 x 155 mm

Related Subjects

Computers and Internet » Artificial Intelligence » General
Computers and Internet » Computers Reference » General
Science and Mathematics » Mathematics » History

Intelligent Systems Reference Library #8: Knowledge Seeker - Ontology Modelling for Information Search and Management: A Compendium New Hardcover
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Product details 263 pages Springer - English 9783642179150 Reviews:
"Synopsis" by , 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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