A novel composite kernel approach to chinese entity relation extraction

Ji Zhang, You Ouyang, Wenjie Li, Yuexian Hou

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

11 Citations (Scopus)


Relation extraction is the task of finding semantic relations between two entities from the text. In this paper, we propose a novel composite kernel for Chinese relation extraction. The composite kernel is defined as the combination of two independent kernels. One is the entity kernel built upon the non-content-related features. The other is the string semantic similarity kernel concerning the content information. Three combinations, namely linear combination, semi-polynomial combination and polynomial combination are investigated. When evaluated on the ACE 2005 Chinese data set, the results show that the proposed approach is effective.
Original languageEnglish
Title of host publicationComputer Processing of Oriental Languages
Subtitle of host publicationLanguage Technology for the Knowledge-based Economy - 22nd International Conference, ICCPOL 2009, Proceedings
Number of pages12
Publication statusPublished - 9 Nov 2009
Event22nd International Conference on Computer Processing of Oriental Languages, ICCPOL 2009 - , Hong Kong
Duration: 26 Mar 200927 Mar 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5459 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference22nd International Conference on Computer Processing of Oriental Languages, ICCPOL 2009
Country/TerritoryHong Kong


  • Composite Kernel
  • Entity Kernel
  • Kernel-based Chinese Relation Extraction
  • String Semantic Similarity Kernel

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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