情境中的模糊計算本體（英文版）

定　價：￥49.00

作　者：	蔡毅，歐陽靖民，梁浩鋒著
出版社：	高等教育出版社
叢編項：
標　簽：	人工智能

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ISBN：	9787040338898	出版時間：	2011-12-23	包裝：	精裝
開本：	16開	頁數：	202	字數：

內容簡介

　　計算本體（computational ontology）是對概念以及概念間的各種關系的一種形式化表述，是知識表示、語義網、智能主體等人工智能主要研究領域中的重要研究對象?！肚榫持械哪：嬎惚倔w（英文版）》提出了一個基于模糊集的、可表達對象對于概念的歸屬程度（object membership）和對象在概念中的典型程度（object typicality）的形式化計算本體模型，以具體例子論證了此形式化模型的必要性和重要性；指出了情境（context）對物體歸屬程度和典型程度的影響，并對此加以形式化；最后討論了此形式化模型在推薦系統(tǒng)中的應用，用實驗證明利用對象典型程度，或把對象典型程度加到協(xié)同過濾法后，能進一步提高模型的準確性。

作者簡介

暫缺《情境中的模糊計算本體（英文版）》作者簡介

圖書目錄

Chapter 1 Introduction
1.1 Semantic Web and Ontologies
1.2 Motivations
1.2.1 Fuzziness of Concepts
1.2.2 Typicality of Objects in Concepts
1.2.3 Context and Its Efiect on Reasoning
1.3 Our Work
1.3.1 Objectives
1.3.2 Contributions
1.4 Structure of the Book
References
Chapter 2 Knowledge Representation on the Wleb
2.1 Semantic Web
2.2 Ontologies
2.3 Description Logics
References
Chapter 3 Concepts and Categorization from a Psychological Perspective
3.1 Theory of Concepts
3.1.1 Classical View
3.1.2 Prototype View
3.1.3 Other Views
3.2 Membership versus Typicality
3.3 Similarity Between Concepts
3.4 Context and Context Efiects
References
Chapter 4 Modeling Uncertainty in Knowledge
Representation
4.1 Fuzzy Set Theory
4.2 Uncertainty in Ontologies and Description Logics
4.3 Semantic Similarity
4.4 Contextual Reasoning
4.5 Summary
References
Chapter 5 Fuzzy Ontology：A First Formal Model
5.1 Rationale
5.2 Concepts and Properties
5.3 Subsumption of Concepts
5.4 Object Membership of an Individual in a Concept
5.5 Prototype Vector and Typicality
5.6 An Example
5.7 Properties of the Proposed Model
5.7.1 Object Membership
5.7.2 Typicality
5.8 On Object Membership and Typicality
5.9 Summary
References
Chapter 6 A More General Ontology Model with ObjectMembership and Typicality
6.1 Motivation
6.2 Limitations of Previous Models
6.2.1 Limitation of Previous Modds in Measuring Object Membership
6.2.2 Limitations of Previous Models in Measuring Object Typicality
6.3 A Better Conceptual Model of Fuzzy Ontology
6.3.1 A Novel Fuzzy Ontology Model
6.3.2 Two Kinds of Measurements of Objects Possessing Properties
6.3.3 Concepts Represented by N-Properties and L-Properties
6.4 Fuzzy Membership of Objects in Concepts
6.4.1 Measuring Degrees of Objects Possessing Defining Properties of Concepts
……
Chapter 7 Context-aware Object Typicality Measurement in Fuzzy Ontology
Chapter 8 Object Membership with Property Importance and Property Priority
Chapter 9 Applications
Chapter 10 Conclusions and Future Work
Index