Marcin Pietranik – författare

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 FeaturesIncludes 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.

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 FeaturesIncludes 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.

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.

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.

This volume constitutes the refereed proceedings of the 12th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2020, held in Phuket, Thailand, in March 2020. The total of 50 full papers accepted for publication in these proceedings were carefully reviewed and selected from 180 submissions. The papers are organized in the following topical sections: ​advanced big data, machine learning and data mining; industry applications of intelligent methods and systems; artificia intelligence, optimization, and databases in practical applications; intelligent applications of internet of things; recommendation and user centric applications of intelligent systems.

This volume constitutes the refereed proceedings of the 12th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2020, held in Phuket, Thailand, in March 2020. 

The total of 50 full papers accepted for publication in these proceedings were carefully reviewed and selected from 180 submissions. The papers are organized in the following topical sections: ​advanced big data, machine learning and data mining; industry applications of intelligent methods and systems; artificia intelligence, optimization, and databases in practical applications; intelligent applications of internet of things; recommendation and user centric applications of intelligent systems.

This book constitutes the refereed proceedings of the 14th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2022, held in Ho Chi Minh City, Vietnam, in November 2022.  ​This volume contains 60 peer-reviewed papers selected for poster presentation from 406 submissions. Papers included in this volume cover the following topics: data mining and machine learning methods, advanced data mining techniques and applications, intelligent and contextual systems, natural language processing, network systems and applications, computational imaging and vision, decision support and control systems, and data modeling and processing for industry 4.0.