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Knowledge Seeker - Ontology Modelling for Information Search and Management

A Compendium

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

Part of the Intelligent Systems Reference Library book series (ISRL, volume 8)

Table of contents

  1. Front Matter
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. Edward H. Y. Lim, James N. K. Liu, Raymond S. T. Lee
      Pages 3-12
    3. Edward H. Y. Lim, James N. K. Liu, Raymond S. T. Lee
      Pages 13-25
    4. Edward H. Y. Lim, James N. K. Liu, Raymond S. T. Lee
      Pages 27-36
    5. Edward H. Y. Lim, James N. K. Liu, Raymond S. T. Lee
      Pages 37-46
  3. KnowledgeSeeker: An Ontology Modeling and Learning Framework

    1. Front Matter
      Pages 47-47
    2. Edward H. Y. Lim, James N. K. Liu, Raymond S. T. Lee
      Pages 49-70
    3. Edward H. Y. Lim, James N. K. Liu, Raymond S. T. Lee
      Pages 71-98
    4. Edward H. Y. Lim, James N. K. Liu, Raymond S. T. Lee
      Pages 99-119
    5. Edward H. Y. Lim, James N. K. Liu, Raymond S. T. Lee
      Pages 121-142
  4. KnowledgeSeeker Applications

    1. Front Matter
      Pages 143-143
    2. Edward H. Y. Lim, James N. K. Liu, Raymond S. T. Lee
      Pages 145-164
    3. Edward H. Y. Lim, James N. K. Liu, Raymond S. T. Lee
      Pages 181-194
  5. Back Matter

About this book

Introduction

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.

Keywords

Computational Intelligence knowledge seeker ontology learning ontology modelling

Authors and affiliations

  • Edward H. Y. Lim
    • 1
  • James N. K. Liu
    • 1
  • Raymond S. T. Lee
    • 2
  1. 1.Department of ComputingThe Hong Kong Polytechnic University Hung Hom, KowloonHong Kong
  2. 2.IATOPIA Research Lab Tsim Sha Tsui, KowloonHong Kong

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-17916-7
  • Copyright Information Springer-Verlag Berlin Heidelberg 2011
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-17915-0
  • Online ISBN 978-3-642-17916-7
  • Series Print ISSN 1868-4394
  • Series Online ISSN 1868-4408
  • Buy this book on publisher's site