Simple Window Selection Strategies for the Simplified Lesk Algorithm for Word Sense Disambiguation

  • Francisco Viveros-Jiménez
  • Alexander Gelbukh
  • Grigori Sidorov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8265)


The Simplified Lesk Algorithm (SLA) is frequently used for word sense disambiguation. It disambiguates by calculating the overlap of a set of dictionary definitions (senses) and the context words. The algorithm is simple and fast, but it has relatively low accuracy. We propose simple strategies for the context window selection that improve the performance of the SLA: (1) constructing the window only with words that have an overlap with some sense of the target word, (2) excluding the target word itself from matching, and (3) avoiding repetitions in the context window. This paper describes the corresponding experiments. Comparison with other more complex knowledge-based algorithms is presented.


Target Word Word Sense Disambiguation Statistical Machine Translation General Word Window Selection 
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 2013

Authors and Affiliations

  • Francisco Viveros-Jiménez
    • 1
  • Alexander Gelbukh
    • 1
    • 2
  • Grigori Sidorov
    • 1
    • 2
  1. 1.Centro de Investigación en Computación, Instituto Politécnico NacionalMexico CityMexico
  2. 2.Institute for Modern Linguistic Research“Sholokhov” Moscow State University for HumanitiesMoscowRussia

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