Serelex: Search and Visualization of Semantically Related Words

  • Alexander Panchenko
  • Pavel Romanov
  • Olga Morozova
  • Hubert Naets
  • Andrey Philippovich
  • Alexey Romanov
  • Cédrick Fairon
Conference paper

DOI: 10.1007/978-3-642-36973-5_97

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7814)
Cite this paper as:
Panchenko A. et al. (2013) Serelex: Search and Visualization of Semantically Related Words. In: Serdyukov P. et al. (eds) Advances in Information Retrieval. ECIR 2013. Lecture Notes in Computer Science, vol 7814. Springer, Berlin, Heidelberg

Abstract

We present Serelex, a system that provides, given a query in English, a list of semantically related words. The terms are ranked according to an original semantic similarity measure learnt from a huge corpus. The system performs comparably to dictionary-based baselines, but does not require any semantic resource such as WordNet. Our study shows that users are completely satisfied with 70% of the query results.

Keywords

semantic similarity measure visualization extraction 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Alexander Panchenko
    • 1
    • 2
  • Pavel Romanov
    • 2
  • Olga Morozova
    • 1
  • Hubert Naets
    • 1
  • Andrey Philippovich
    • 2
  • Alexey Romanov
    • 2
  • Cédrick Fairon
    • 1
  1. 1.Université catholique de LouvainLouvain-la-NeuveBelgium
  2. 2.Bauman Moscow State Technical UniversityMoscowRussia

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