Term Set Expansion based on Multi-Context Term Embeddings: an End-to-end Workflow

Jonathan Mamou, Oren Pereg, Moshe Wasserblat, Ido Dagan, Yoav Goldberg, Alon Eirew, Yael Green, Shira Guskin, Peter Izsak, Daniel Korat

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

We present SetExpander, a corpus-based system for expanding a seed set of terms into a more complete set of terms that belong to the same semantic class. SetExpander implements an iterative end-to end workflow for term set expansion. It enables users to easily select a seed set of terms, expand it, view the expanded set, validate it, re-expand the validated set and store it, thus simplifying the extraction of domain-specific fine-grained semantic classes. SetExpander has been used for solving real-life use cases including integration in an automated recruitment system and an issues and defects resolution system.

Original languageEnglish
Title of host publicationCOLING 2018 - 27th International Conference on Computational Linguistics, Proceedings of System Demonstrations
PublisherAssociation for Computational Linguistics (ACL)
Pages58-62
Number of pages5
ISBN (Electronic)9781948087537
StatePublished - 1 Jan 2018
Externally publishedYes
Event27th International Conference on Computational Linguistics, COLING 2018 - Santa Fe, United States
Duration: 20 Aug 201826 Aug 2018

Publication series

NameCOLING 2018 - 27th International Conference on Computational Linguistics, Proceedings of System Demonstrations

Conference

Conference27th International Conference on Computational Linguistics, COLING 2018
Country/TerritoryUnited States
CitySanta Fe
Period20/08/1826/08/18

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Language and Linguistics
  • Linguistics and Language

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