Resolving entity morphs in censored data

Hongzhao Huang, Zhen Wen, Dian Yu, Heng Ji, Yizhou Sun, Jiawei Han, He Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In some societies, internet users have to create information morphs (e.g. "Peace West King" to refer to "Bo Xilai") to avoid active censorship or achieve other communication goals. In this paper we aim to solve a new problem of resolving entity morphs to their real targets. We exploit temporal constraints to collect crosssource comparable corpora relevant to any given morph query and identify target candidates. Then we propose various novel similarity measurements including surface features, meta-path based semantic features and social correlation features and combine them in a learning-to-rank framework. Experimental results on Chinese Sina Weibo data demonstrate that our approach is promising and significantly outperforms baseline methods 1.

Original languageEnglish (US)
Title of host publicationLong Papers
PublisherAssociation for Computational Linguistics (ACL)
Pages1083-1093
Number of pages11
ISBN (Print)9781937284503
StatePublished - Jan 1 2013
Event51st Annual Meeting of the Association for Computational Linguistics, ACL 2013 - Sofia, Bulgaria
Duration: Aug 4 2013Aug 9 2013

Publication series

NameACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference
Volume1

Other

Other51st Annual Meeting of the Association for Computational Linguistics, ACL 2013
CountryBulgaria
CitySofia
Period8/4/138/9/13

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language

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