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WebKnox: Web Knowledge Extraction

This thesis focuses on entity and fact extraction from the web. Different knowledge representations and techniques for information extraction are discussed before the design for a knowledge extraction system, called WebKnox, is introduced. The main contribution of this thesis is the trust ranking of extracted facts with a self-supervised learning loop and the extraction system with its composition of known and refined extraction algorithms. The used
techniques show an improvement in precision and recall in most of the matters for entity and fact extractions compared to the chosen baseline approaches.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa.de:bsz:14-qucosa-23766
Date21 August 2009
CreatorsUrbansky, David
ContributorsTechnische Universität Dresden, Fakultät Informatik, Dipl. Inf. Marius Feldmann, Prof. Dr. rer. nat. habil. Dr. h.c. Alexander Schill
PublisherSaechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
Languagedeu
Detected LanguageEnglish
Typedoc-type:masterThesis
Formatapplication/pdf

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