
Contents
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22.1 Introduction 22.1 Introduction
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22.2 Anatomy of an Ontology 22.2 Anatomy of an Ontology
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22.2.1 Building Blocks of an Ontology 22.2.1 Building Blocks of an Ontology
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22.2.2 Sections of an Ontology 22.2.2 Sections of an Ontology
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22.3 Ontologies under Different Lenses 22.3 Ontologies under Different Lenses
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22.3.1 Computer Science vs Philosophy 22.3.1 Computer Science vs Philosophy
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22.3.2 Ontologies and the Semantic Web 22.3.2 Ontologies and the Semantic Web
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22.3.3 Ontologies and the Lexicon 22.3.3 Ontologies and the Lexicon
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22.3.4 Ontologies and Graphs 22.3.4 Ontologies and Graphs
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22.3.5 Ontologies and Software Engineering 22.3.5 Ontologies and Software Engineering
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22.4 Existing Ontologies 22.4 Existing Ontologies
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22.4.1 Upper Ontologies 22.4.1 Upper Ontologies
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22.4.2 Middle Ontologies 22.4.2 Middle Ontologies
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22.4.3 Domain Ontologies 22.4.3 Domain Ontologies
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22.5 Ontology Building vs Ontology Learning 22.5 Ontology Building vs Ontology Learning
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22.5.1 Building 22.5.1 Building
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22.5.2 Learning 22.5.2 Learning
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22.5.3 Maintenance 22.5.3 Maintenance
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22.6 Ontology Matching, Mapping, and Merging 22.6 Ontology Matching, Mapping, and Merging
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22.7 Interfaces 22.7 Interfaces
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22.8 Ontology Languages 22.8 Ontology Languages
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22.9 Evaluation 22.9 Evaluation
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22.10 Applications 22.10 Applications
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22.10.1 Semantic Web 22.10.1 Semantic Web
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22.10.2 Word Sense Disambiguation 22.10.2 Word Sense Disambiguation
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22.10.3 Automated Reasoning 22.10.3 Automated Reasoning
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22.10.4 Question Answering 22.10.4 Question Answering
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22.10.5 Semantic Information Retrieval 22.10.5 Semantic Information Retrieval
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22.10.6 Content-Based Social Network Analysis 22.10.6 Content-Based Social Network Analysis
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22.10.7 Machine Translation 22.10.7 Machine Translation
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22.10.8 Electronic Lexicography 22.10.8 Electronic Lexicography
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22.11 Conclusions 22.11 Conclusions
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Further Reading and Relevant Resources Further Reading and Relevant Resources
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Acknowledgements Acknowledgements
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References References
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22 Ontologies
Get accessRoberto Navigli is Professor of Computer Science at the Sapienza University of Rome, where he heads the multilingual Natural Language Processing group. He is one of the few researchers to have received two ERC grants (on multilingual word sense disambiguation and multilingual language-independent open-text unified representations). In 2015 he received the META prize for overcoming language barriers with BabelNet, a project also highlighted in The Guardian and Time magazine, and winner of the Artificial Intelligence Journal prominent paper award in 2017. He is the co-founder of Babelscape, a company which enables NLP in dozens of languages.
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Published:07 April 2016
Cite
Abstract
This chapter is about ontologies: that is, knowledge models of a domain of interest. We introduce ontologies, its building blocks and sections, view them from the perspective of several fields of knowledge (computer science, philosophy, software engineering, etc.), and present existing ontologies and the different tasks of ontology building, learning, matching, mapping, and merging. We also review interfaces for building ontologies and the knowledge representation languages used to implement them. Finally, we discuss the different ways of evaluating an ontology and the applications in which it can be used, including word sense disambiguation, reasoning, question answering, semantic information retrieval. and machine translation.
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