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Programming and Computer Software

, Volume 41, Issue 6, pp 336–349 | Cite as

Methods for automatic term recognition in domain-specific text collections: A survey

  • N. A. AstrakhantsevEmail author
  • D. G. Fedorenko
  • D. Yu. Turdakov
Article
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Abstract

Applications related to domain specific text processing often use glossaries and ontologies, and the main step of such resource construction is term recognition. This paper presents a survey of existing definitions of the term and its linguistic features, formulates the task definition for term recognition, and analyzes presently-available methods for automatic term recognition, such as methods for candidates collection, methods based on statistics and contexts of term occurrences, methods using topic models, and methods based on external resources (such as text collections from other domains, ontologies, and Wikipedia). This paper also provides an overview of standard methodologies and datasets for experimental research.

Keywords

Semantic Relatedness Topic Model Term Frequency Term Candidate Computational Linguistics 
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

© Pleiades Publishing, Ltd. 2015

Authors and Affiliations

  • N. A. Astrakhantsev
    • 1
    Email author
  • D. G. Fedorenko
    • 1
  • D. Yu. Turdakov
    • 1
  1. 1.Institute for System ProgrammingRussian Academy of SciencesMoscowRussia

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