Topic Models Can Improve Domain Term Extraction

  • Elena Bolshakova
  • Natalia Loukachevitch
  • Michael Nokel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7814)


The paper describes the results of an experimental study of topic models applied to the task of single-word term extraction. The experiments encompass several probabilistic and non-probabilistic topic models and demonstrate that topic information improves the quality of term extraction, as well as NMF with KL-divergence minimization is the best among the models under study.


Topic Models Clustering Single-Word Term Extraction 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Elena Bolshakova
    • 1
  • Natalia Loukachevitch
    • 2
  • Michael Nokel
    • 1
  1. 1.Moscow State UniversityRussian Federation
  2. 2.Research Computing CenterMoscow State UniversityRussian Federation

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