Ontology Supported Automatic Generation of High-Quality Semantic Metadata

  • Ümit Yoldas
  • Gábor Nagypál
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4275)


Large amounts of data in modern information systems, such as the World Wide Web, require innovative information retrieval techniques to effectively satisfy users’ information need. A promising approach is to exploit document semantics in the IR process. For this purpose, high-quality semantic metadata is needed. This paper introduces a method to automatically create semantic metadata by using ontologically enhanced versions of common information extraction methods, such as named entity recognition and coreference resolution. Furthermore, this work also proposes the application of ontology-specific heuristic rules to further improve the quality of generated metadata. The results of our method was evaluated using a small test collection.


Vector Space Model Heuristic Rule Information Retrieval System Name Entity Recognition Name Entity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ümit Yoldas
    • 1
  • Gábor Nagypál
    • 2
  1. 1.Conemis AGKarlsruheGermany
  2. 2.FZI Research Center for Information Technologies, at the University of KarlsruheKarlsruheGermany

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