Knowledge Seeker - Ontology Modelling for Information Search and Management

A Compendium
1. Auflage 2011
ISBN: 978-3-642-17916-7
Verlag: Springer
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 237 Seiten

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.

Autoren/Hrsg.

Inhaltsverzeichnis

1;Title;1
2;Preface;5
3;Contents;9
4;Part I Introduction;23
4.1;Chapter 1 Computational Knowledge and Ontology;24
4.1.1;What Is Knowledge?;24
4.1.2;Computational Knowledge in Information Systems;24
4.1.2.1;Knowledge Engineering;25
4.1.2.2;Knowledge Representation;25
4.1.3;What Is Ontology?;27
4.1.4;Ontology Modeling in Computer Systems;28
4.1.4.1;Computational Ontology Representation;28
4.1.4.2;Top-Level Ontologies;29
4.1.4.3;Lexical Ontologies;30
4.1.4.4;Domain Ontologies;32
4.2;Chapter 2 Ontology Engineering;34
4.2.1;Introduction;34
4.2.2;Ontology Fundamentals;35
4.2.2.1;Ontological Structure;35
4.2.2.2;Ontological Taxonomy;36
4.2.2.3;Ontological Relations;37
4.2.2.4;Lexical Relations;39
4.2.3;Ontology Engineering Tools;40
4.2.3.1;Protégé Ontology Editor;41
4.2.4;Ontology Learning from Text;42
4.2.4.1;Learning Terminology;44
4.2.4.2;Learning Taxonomy;46
4.3;Chapter 3 Text Information Retrieval;47
4.3.1;Information Retrieval Model;47
4.3.1.1;Term Weighting Model;47
4.3.1.2;Text Classification;48
4.3.1.3;Text Clustering;51
4.3.2;Feature Selection and Reduction;52
4.3.3;Search Engine Modeling;54
4.3.4;Evaluation Methods;55
4.3.4.1;Performance Measurement;56
4.4;Chapter 4 Web Data Semantics;57
4.4.1;Semantic Web;57
4.4.1.1;W3C Semantic Web;59
4.4.2;Semantic Modeling;60
4.4.2.1;Taxonomy;61
4.4.2.2;Thesaurus;61
4.4.2.3;Topic Maps;62
4.4.2.4;Ontology;63
4.4.2.5;Ontology Languages for the Semantic Web;64
4.4.3;Semantic Annotation and Information Retrieval;66
5;Part II KnowledgeSeeker: An Ontology Modeling and Learning Framework;67
5.1;Chapter 5 Ontology Modeling Framework;68
5.1.1;KnowledgeSeeker – The System Overviews;68
5.1.2;Background of Signs System and Ontology;70
5.1.2.1;The Semiotics;70
5.1.2.2;The Sign System for Concept Formation;73
5.1.2.3;The Meaning of Words;75
5.1.2.4;The Semantics of Relations;76
5.1.3;Ontology Graph Overviews;78
5.1.3.1;Nodes in Ontology Graph;79
5.1.3.2;Term Nodes in Ontology Graph;81
5.1.3.3;Words Function;83
5.1.4;The Implementation of Ontology Graph;87
5.1.4.1;The Conceptual Structure of Ontology Graph;87
5.1.4.2;The Class Diagram of Ontology Graph;88
5.2;Chapter 6 Ontology Learning in Chinese Text;90
5.2.1;The Ontology Learning Method;90
5.2.1.1;Term Extraction;91
5.2.1.2;Term-to-Class Relationship Mapping;92
5.2.1.3;Term-to-Term Relationship Mapping;100
5.2.1.4;Concept Clustering;110
5.2.1.5;Sample Result of Domain Ontology Graph Generation (10 Domains);115
5.3;Chapter 7 Ontology Graph Generation Process;118
5.3.1;Ontology in Information Systems;118
5.3.2;Ontology Graph Generation Process in KnowledgeSeeker;119
5.3.2.1;Definition of Ontology Graph Structure;120
5.3.2.2;Domain Ontology Graph Generation Process;122
5.3.2.3;Document Ontology Graph Generation;124
5.3.3;Automatic Generation of Domain Ontology Graph;126
5.3.3.1;Experimental Setup;127
5.3.3.2;Experimental Results;129
5.4;Chapter 8 Ontology Graph Operations;139
5.4.1;Ontology Graph Matching and Querying Process;139
5.4.2;Introduction to Ontology Matching and Mapping;139
5.4.2.1;Ontology Graph Matching Methods;140
5.4.3;Matching Different Components with Ontology Graph;142
5.4.3.1;Matching Terms to Domain Ontology Graph;143
5.4.3.2;Matching Text Document to Domain Ontology Graph;146
5.4.3.3;Ontology Graph Based Similarity Measurement;150
5.4.3.4;Matching Two Document Ontology Graphs;152
5.4.4;Overviews of Ontology Graph Based Querying;155
5.4.4.1;Ontology Graph Querying Methods;155
5.4.5;Operations in Ontology Graph Based Querying;155
5.4.5.1;Querying Document with Document Ontology Graph;156
6;Part III KnowledgeSeeker: Applications;161
6.1;Chapter 9 Ontology Graph Based Approach for Automatic Chinese Text Classification;162
6.1.1;Introduction;162
6.1.2;Methodologies;164
6.1.2.1;Ontology Graphs Reviews;164
6.1.2.2;Classification Algorithm;165
6.1.3;Experiments;166
6.1.3.1;Experiments Description;167
6.1.3.2;Evaluation Method;168
6.1.3.3;Performance on Ontology Graph Based Text Classification;169
6.1.3.4;Experimental Results;170
6.2;Chapter 10 IATOPIA iCMS KnowledgeSeeker – An Integrated Content Management System and Digital Asset Management System (DAMS);182
6.2.1;IATOPIA iCMS KnowledgeSeeker;182
6.2.1.1;System Features;182
6.2.1.2;System Model and Architecture;183
6.2.1.3;Ontology System;185
6.2.1.4;Search Indexing System;185
6.2.1.5;IATOPIA Search Engine;186
6.2.2;IATOPIA Digital Asset Management System (DAMS);187
6.2.2.1;DAMS System Architecture Overview;187
6.2.2.2;IATOIPA iCMS Databank Cluster in DAMS;187
6.2.2.3;Ontology System in DAMS;188
6.2.2.4;DAMS and Web Channel Interface Examples;189
6.3;Chapter 11 IATOPIA News Channel (IAToNews) – An Intelligent Ontological Agent-Based Web News Retrieval and Search System;191
6.3.1;Introduction;191
6.3.2;IAToNews System Architecture Overview;191
6.3.3;Ontology System in IAToNews;192
6.3.3.1;Article Ontology;193
6.3.3.2;Topic Ontology;194
6.3.3.3;Ontology Based Content Indexing;194
6.3.4;IAToNews Web Interface Examples;195
6.4;Chapter 12 Collaborative Content and User-Based Web Ontology Learning System;197
6.4.1;Introduction;197
6.4.2;Background;198
6.4.2.1;Problem of Building a Generalized Ontology to Satisfy Daily Life;198
6.4.2.2;Semantic web;198
6.4.2.3;Web Channels;198
6.4.2.4;BuBo (Feedback, Personalization with User Ontology);199
6.4.3;Methodology;199
6.4.3.1;Overview of System Architecture;199
6.4.3.2;Content-Based Ontology Learning Process;200
6.4.3.3;User-Based ontology Personalization Process;203
6.4.4;Implementation;208
6.4.4.1;Architecture of the Collaborative System Implementation;208
6.4.4.2;Structure of the Specified Domains Ontology with Generalized OG;209
6.4.4.3;Ontology-Based Search Engine within BuBo;210
6.4.5;Conclusions;210
7;References;211