Unsupervised Keyphrase Extraction for Search Ontologies

  • Jon Atle Gulla
  • Hans Olaf Borch
  • Jon Espen Ingvaldsen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3999)


Ontology learning today ranges from simple frequency counting methods to advanced linguistic analyses of sentence structure and word semantics. For ontologies in information retrieval systems, class concepts and hierarchical relationships at the appropriate level of detail are crucial to the quality of retrieval. In this paper, we present an unsupervised keyphrase extraction system and evaluate its ability to support the construction of ontologies for search applications. In spite of its limitations, such a system is well suited to constantly changing domains and captures some interesting domain features that are important in search ontologies. The approach is evaluated against the project management documentation of a Norwegian petroleum company.


Information Retrieval System Ontology Concept Candidate Phrase Search Application Project Scope 
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

  • Jon Atle Gulla
    • 1
  • Hans Olaf Borch
    • 1
  • Jon Espen Ingvaldsen
    • 1
  1. 1.Department of Computer and Information ScienceNorwegian University of Science and TechnologyTrondheimNorway

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