Formal Methods for Managing and Processing Ontology Alignments

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Formal Methods for Managing and Processing Ontology Alignments

Pietranik, Marcin

ウェブストア価格 ¥25,681（本体¥23,347）
CRC Press（2024/10発売）
外貨定価 US$ 120.00
ポイント 233pt

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製本 Hardcover:ハードカバー版／ページ数 193 p.
言語 ENG
商品コード 9781032571171
DDC分類 006.332

Full Description

Ontologies are formal knowledge representation methods that can provide means for a shared understanding of a given domain. To enable meaningful communication and interoperability between two or more information systems that utilize independently created ontologies, a bridge between them is necessary, often referred to as an ontology alignment. Formal Methods for Managing and Processing Ontology Alignments provides complete ontology alignment lifecycle, including modelling, methods, and maintenance processes.

Summarizing the author's research from the past ten years, this book consolidates findings previously published in prestigious international journals and presented at leading conferences. Each chapter is designed to be self-contained, allowing readers to approach the material modularly. The text introduces basic mathematical concepts, and later chapters build upon these foundations, but each focuses on specific aspects of ontology alignment, making the content accessible and easy to follow.

Key Features

Includes formal definitions of ontologies and ontology alignment along with a set of methods for providing semantics of attributes and relations.
Provides application of fuzzy logic in the task of ontology alignment.
Contains methods of managing the evolution of ontologies and their alignments.
Proposes novel methods of assessing the quality ontology alignment.

Situated in the fields of knowledge representation and semantic technologies, this book is an invaluable resource for both academic researchers and practitioners, as well as students looking to deepen their understanding.

1. Introduction. 2. A formal model of ontology and ontology alignment. 3. Classification of ontology alignment techniques. 4. Fuzzy logic framework for ontology alignment. 5. Ontology evolution and version management in ontology alignment. 6. Advanced methods of assessing ontology alignment. 7. Conclusions.