Part3 chapter2

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Information Extraction for Ontology Learning
Authors Fabian SUCHANEK
Part Lexical Learning
Topics Information Extraction
Projects YAGO
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Information Extraction for Ontology Learning

The chapter "Information Extraction for Ontology Learning" was written by Fabian SUCHANEK.

Abstract

In this chapter, we discuss how ontologies can be constructed by extracting information from Web documents. This is a challenging task, because information extraction is usually a noisy endeavor, whereas ontologies usually require clean and crisp data. This means that the extracted information has to be cleaned, disambiguated, and made logically consistent to some degree. We will discuss three approaches that extract an ontology in this spirit from Wikipedia (DBpedia, YAGO, and KOG). We will also present approaches that aim to extract an ontology from natural language documents or, by extension, from the entire Web (OntoUSP, NELL and SOFIE).We will show that information extraction and ontology construction can enter into a fruitful reinforcement loop, where more extracted information leads to a larger ontology, and a larger ontology helps extracting more information.

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Facts about Part3 chapter2RDF feed
AbstractIn this chapter, we discuss how ontologies In this chapter, we discuss how ontologies can be constructed by extracting information from Web documents. This is a challenging task, because information

extraction is usually a noisy endeavor, whereas ontologies usually require clean and crisp data. This means that the extracted information has to be cleaned, disambiguated, and made logically consistent to some degree. We will discuss three approaches that extract an ontology in this spirit from Wikipedia (DBpedia,

YAGO, and KOG). We will also present approaches that aim to extract an ontology from natural language documents or, by extension, from the entire Web (OntoUSP, NELL and SOFIE).We will show that information extraction and ontology construction can enter into a fruitful reinforcement loop, where more extracted information leads to a larger ontology, and a larger ontology helps extracting more information.
ntology helps extracting more information.
AuthorFabian SUCHANEK  +
Book part titleLexical Learning  +
Chapter titleInformation Extraction for Ontology Learning  +
ProjectsYAGO  +
TopicsInformation Extraction  +
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