Named Entity Recognition in Turkish with Bayesian Learning and Hybrid Approaches


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RehaYavuz S., Kucuk D., YAZICI A.

28th International Symposium on Computer and Information Sciences (ISCIS), Paris, France, 28 - 29 October 2013, vol.264, pp.129-138 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 264
  • Doi Number: 10.1007/978-3-319-01604-7_13
  • City: Paris
  • Country: France
  • Page Numbers: pp.129-138

Abstract

Named entity recognition is one of the significant textual information extraction tasks. In this paper, we present two approaches for named entity recognition on Turkish texts. The first is a Bayesian learning approach which is trained on a considerably limited training set. The second approach comprises two hybrid systems based on joint utilization of this Bayesian learning approach and a previously proposed rule-based named entity recognizer. All of the proposed three approaches achieve promising performance rates. This paper is significant as it reports the first use of the Bayesian approach for the task of named entity recognition on Turkish texts for which especially practical approaches are still insufficient.