Dependency tree based Chinese relation extraction over web data

Shanshan Zheng, Jing Yang, Xin Lin, Jun Zhong Gu

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

Abstract

A new semi-supervised approach for Chinese relation extraction (RE) over constantly growing and edgeless web data is introduced in this paper. Existing semi-supervised approaches have the better improvement potential while lacking syntactic structure and semantic meaning of a sentence and unsuitable to loosely structured Chinese sentences. To follow their basic procedures as well as covering their remaining shortages, a dependency tree (DT) including both structure and semantic information is drawn in. Based on DTs, a new kind of pattern, called DT-based pattern, is proposed to extract new triples. Later patterns are optimized according to the characteristics of Chinese and typed dependency trees. Finally, extensive experiments show the higher precision and more efficiency of the proposed approach against DIPRE.

Original languageEnglish
Title of host publicationProceedings - 2012 7th International Conference on Knowledge, Information and Creativity Support Systems, KICSS 2012
Pages104-110
Number of pages7
DOIs
StatePublished - 2012
Event2012 7th International Conference on Knowledge, Information and Creativity Support Systems, KICSS 2012 - Melbourne, VIC, Australia
Duration: 8 Nov 201210 Nov 2012

Publication series

NameProceedings - 2012 7th International Conference on Knowledge, Information and Creativity Support Systems, KICSS 2012

Conference

Conference2012 7th International Conference on Knowledge, Information and Creativity Support Systems, KICSS 2012
Country/TerritoryAustralia
CityMelbourne, VIC
Period8/11/1210/11/12

Keywords

  • DT-based pattern
  • Dependency tree
  • Relation extraction
  • Semi-supervised

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