Chinese abbreviation-definition identification: a SVM approach using context information

  • Authors:
  • Xu Sun;Houfeng Wang;Yu Zhang

  • Affiliations:
  • Department of Computer Science and Technology, School of Electronic Engineering and Computer Science, Peking University, Beijing, China;Department of Computer Science and Technology, School of Electronic Engineering and Computer Science, Peking University, Beijing, China;Department of Computer Science and Technology, School of Electronic Engineering and Computer Science, Peking University, Beijing, China

  • Venue:
  • PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
  • Year:
  • 2006

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Abstract

As a special form of unknown words, Chinese abbreviations represent significant problems for Chinese text processing. The goal of this study is to automatically find the definition for a Chinese abbreviation in the context where both the abbreviation and its definition occur, enforcing the constraint of one sense per discourse for an abbreviation. First, the candidate abbreviation-definition pairs are collected, and then a SVM approach using context information is employed to classify candidate abbreviation-definition pairs so that the pairs can be identified. The performance of the approach is evaluated on a manually annotated test corpus, and is also compared with two other machine learning approaches: Maximum Entropy and Decision Tree. Experimental results show that our approach reaches a good performance.