Learning Ontology Relations by Combining Corpus-Based Techniques and Reasoning on Data from Semantic Web Sources
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Home > Computing and Information Technology > Business applications > Enterprise software > Learning Ontology Relations by Combining Corpus-Based Techniques and Reasoning on Data from Semantic Web Sources: (44 Forschungsergebnisse der Wirtschaftsuniversitaet Wien)
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Learning Ontology Relations by Combining Corpus-Based Techniques and Reasoning on Data from Semantic Web Sources: (44 Forschungsergebnisse der Wirtschaftsuniversitaet Wien)

Learning Ontology Relations by Combining Corpus-Based Techniques and Reasoning on Data from Semantic Web Sources: (44 Forschungsergebnisse der Wirtschaftsuniversitaet Wien)


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About the Book

The manual construction of formal domain conceptualizations (ontologies) is labor-intensive. Ontology learning, by contrast, provides (semi-)automatic ontology generation from input data such as domain text. This thesis proposes a novel approach for learning labels of non-taxonomic ontology relations. It combines corpus-based techniques with reasoning on Semantic Web data. Corpus-based methods apply vector space similarity of verbs co-occurring with labeled and unlabeled relations to calculate relation label suggestions from a set of candidates. A meta ontology in combination with Semantic Web sources such as DBpedia and OpenCyc allows reasoning to improve the suggested labels. An extensive formal evaluation demonstrates the superior accuracy of the presented hybrid approach.

Table of Contents:
Contents: Ontology learning fundamentals and techniques – Overview of ontology relation detection and labeling methods – A novel hybrid approach for labeling non-taxonomic relations which combines corpus-based methods with ontology reasoning based on Semantic Web sources – Improved accuracy demonstrated with an extensive formal evaluation.

About the Author :
Gerhard Wohlgenannt is a senior researcher at the New Media Technology Department, MODUL University Vienna. He received his PhD from the Institute for Information Business at Vienna University of Economics and Business (WU). His research interests include ontology learning, text mining and the Semantic Web.


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Product Details
  • ISBN-13: 9783631606513
  • Publisher: Peter Lang AG
  • Publisher Imprint: Peter Lang AG
  • Edition: New edition
  • Language: English
  • Series Title: 44 Forschungsergebnisse der Wirtschaftsuniversitaet Wien
  • Width: 148 mm
  • ISBN-10: 3631606516
  • Publisher Date: 13 May 2011
  • Binding: Hardback
  • Height: 210 mm
  • No of Pages: 222
  • Weight: 390 gr


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Learning Ontology Relations by Combining Corpus-Based Techniques and Reasoning on Data from Semantic Web Sources: (44 Forschungsergebnisse der Wirtschaftsuniversitaet Wien)
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Learning Ontology Relations by Combining Corpus-Based Techniques and Reasoning on Data from Semantic Web Sources: (44 Forschungsergebnisse der Wirtschaftsuniversitaet Wien)
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