Taxonomy Matching Using Background Knowledge, Angermann

Автор: Angermann Heiko, Ramzan Naeem
Название: Taxonomy Matching Using Background Knowledge: Linked Data, Semantic Web and Heterogeneous Repositories
ISBN: 331989157X ISBN-13(EAN): 9783319891576
Издательство: Springer
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Цена: 4268.00 р.
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Описание: This important text/reference presents a comprehensive review of techniques for taxonomy matching, discussing matching algorithms, analyzing matching systems, and comparing matching evaluation approaches.

Автор: Krig Scott
Название: Computer Vision Metrics: Survery, Taxonomy and Analysis of Computer Vision, Visual Neuroscience, and Deep Learning
ISBN: 3319815954 ISBN-13(EAN): 9783319815954
Издательство: Springer
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Цена: 9756.00 р.
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Описание: Based on the successful 2014 book published by Apress, this textbook edition is expanded to provide a comprehensive history and state-of-the-art survey for fundamental computer vision methods and deep learning.

Название: Ontology learning and knowledge discovery using the web
ISBN: 1609606256 ISBN-13(EAN): 9781609606251
Издательство: Mare Nostrum (Eurospan)
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Цена: 31046.00 р.
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Описание: Provides relevant theoretical foundations, and disseminates new research findings and expert views on the remaining challenges in ontology learning. This book is invaluable resource as a library or personal reference for graduate students, researchers, and industrial practitioners.

Автор: Grzegorz J. Nalepa
Название: Modeling with Rules Using Semantic Knowledge Engineering
ISBN: 3319666541 ISBN-13(EAN): 9783319666549
Издательство: Springer
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Цена: 18294.00 р.
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Описание: Part I Domain of Rule-Based Systems.- Rules as a Knowledge Representation Paradigm.- Knowledge Engineering with Rules.- Selected Applications of Rule.- Part II Formal Models for Rules.- Formalism for Description of Decision Rules.- Formalized Integration of Rules and Processes.- Prototyping Structure of Rule Bases.- Handling Uncertainty in Rules.- Formalizing Interoperability in Rule Bases.- Part III Practical Studies in Semantic Knowledge Engineering.- Semantic Knowledge Engineering Approach.- Rule Interoperability with Expert System Shells.- Visual Software Modeling with Rules.- Using Rules to Support Software Testing.- Integrating Business Process Models with Rules.- Rule-Based Systems and Semantic Web.- Collaborative Knowledge Engineering with Wikis.- Designing Robot Control Logic with Rules.- Rules in Mobile Context-Aware Systems.- Index.