Literatur zur Informationserschließung

Diese Datenbank enthält über 40.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.

© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft / Powered by litecat, BIS Oldenburg (Stand: 28. April 2022)

Suchergebnisse

• 1
  Suchanek, F.M. ; Kasneci, G. ; Weikum, G.: YAGO: a large ontology from Wikipedia and WordNet.
  In: Web semantics: science, services and agents on the World Wide Web. 6(2008) no.3, S.203-217.
  
  Abstract: This article presents YAGO, a large ontology with high coverage and precision. YAGO has been automatically derived from Wikipedia and WordNet. It comprises entities and relations, and currently contains more than 1.7 million entities and 15 million facts. These include the taxonomic Is-A hierarchy as well as semantic relations between entities. The facts for YAGO have been extracted from the category system and the infoboxes of Wikipedia and have been combined with taxonomic relations from WordNet. Type checking techniques help us keep YAGO's precision at 95%-as proven by an extensive evaluation study. YAGO is based on a clean logical model with a decidable consistency. Furthermore, it allows representing n-ary relations in a natural way while maintaining compatibility with RDFS. A powerful query model facilitates access to YAGO's data.
  
  Inhalt: Vgl.: http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B758F-4TDJGCF-1&_user=10&_coverDate=09%2F30%2F2008&_rdoc=1&_fmt=high&_orig=search&_sort=d&_docanchor=&view=c&_searchStrId=1352884236&_rerunOrigin=google&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=3285f9101276b6f41185a30c1b39d1d0.
  
  Themenfeld: Semantic Web ; Wissensrepräsentation
  Objekt: Yago ; Wikipedia ; WordNet
  
  
• 2
  Suchanek, F.M. ; Kasneci, G. ; Weikum, G.: YAGO: a core of semantic knowledge unifying WordNet and Wikipedia.
  In: http://www2007.org/papers/paper391.pdf.
  
  Abstract: We present YAGO, a light-weight and extensible ontology with high coverage and quality. YAGO builds on entities and relations and currently contains more than 1 million entities and 5 million facts. This includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as hasWonPrize). The facts have been automatically extracted from Wikipedia and unified with WordNet, using a carefully designed combination of rule-based and heuristic methods described in this paper. The resulting knowledge base is a major step beyond WordNet: in quality by adding knowledge about individuals like persons, organizations, products, etc. with their semantic relationships - and in quantity by increasing the number of facts by more than an order of magnitude. Our empirical evaluation of fact correctness shows an accuracy of about 95%. YAGO is based on a logically clean model, which is decidable, extensible, and compatible with RDFS. Finally, we show how YAGO can be further extended by state-of-the-art information extraction techniques.
  
  Inhalt: Beitrag für WWW 2007.
  
  Themenfeld: Semantic Web ; Wissensrepräsentation
  Objekt: Yago ; Wikipedia ; WordNet