A delimiter-based general approach for Chinese term extraction

Yuhang Yang, Qin Lu, Tiejun Zhao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

9 Citations (Scopus)

Abstract

This article addresses a two-step approach for term extraction. In the first step on term candidate extraction, a new delimiter-based approach is proposed to identify features of the delimiters of term candidates rather than those of the term candidates themselves.This delimiter-based method is much more stable and domain independent than the previous approaches. In the second step on term verification, an algorithm using link analysis is applied to calculate the relevance between term candidates and the sentences from which the terms are extracted. All information is obtained from the working domain corpus without the need for prior domain knowledge. The approach is not targeted at any specific domain and there is no need for extensive training when applying it to new domains. In other words, the method is not domain dependent and it is especially useful for resource-limited domains. Evaluations of Chinese text in two different domains show quite significant improvements over existing techniques and also verify its efficiency and its relatively domain-independent nature. The proposed method is also very effective for extracting new terms so that it can serve as an efficient tool for updating domain knowledge, especially for expanding lexicons.
Original languageEnglish
Pages (from-to)111-125
Number of pages15
JournalJournal of the American Society for Information Science and Technology
Volume61
Issue number1
DOIs
Publication statusPublished - 1 Jan 2010

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Networks and Communications
  • Artificial Intelligence

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