Journal of Jilin University Science Edition

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Clustering Based Denoising for Aligned Data of Distant Supervision

ZHU Zhaolong, OUYANG Dantong, YE Yuxin   

  1. Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education,College of Computer Science and Technology, Jilin Unive
    rsity, Changchun 130012, China
  • Received:2013-01-31 Online:2014-03-26 Published:2014-03-20
  • Contact: OUYANG Dantong E-mail:ouyd@jlu.edu.cn

Abstract:

A new clustering based denoising method was proposed, with the help of clustering and recognizing patterns of sentences that express a relationship, to reduce the noisy data that was introduced in the alignment step of traditional distant supervision method. The experimental results demonstrate that our approach can significantly improve the accuracy of relation extraction system.

Key words: relation extraction, clustering, distant supervision method, denoising

CLC Number: 

  • TP181