Research on tree kernel-based personal relation extraction

Cheng Peng, Jinghang Gu, Longhua Qian

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

7 Citations (Scopus)

Abstract

In this paper, a kernel-based personal relation extraction method is presented. First, a personal relation corpus is built through filtering and expansion from the ACE2005 Chinese corpus. Then, the structured information, which is appropriate for personal relation extraction, is constructed by applying pruning rules on the basis of the shortest path-enclosed tree. After that,TongYiCi CiLin semantic information is embedded into the structured information. Finally, re-sampling techniques are employed to alleviate the data imbalance problem inherent in the corpus distribution. Experimental results show that, the pruning rules, the embedding of semantic information and the application of re-sampling techniques can improve the F1 score by 3.5, 3.0 and approximate 3.0 units respectively compared with the baseline system. It suggests that the method we propose is effective for personal relation extraction.

Original languageEnglish
Title of host publicationNatural Language Processing and Chinese Computing - First CCF Conference, NLPCC 2012, Proceedings
Pages225-236
Number of pages12
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event1st CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2012 - Beijing, China
Duration: 31 Oct 20125 Nov 2012

Publication series

NameCommunications in Computer and Information Science
Volume333 CCIS
ISSN (Print)1865-0929

Conference

Conference1st CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2012
Country/TerritoryChina
CityBeijing
Period31/10/125/11/12

Keywords

  • personal relation extraction
  • re-sampling
  • social network
  • tongyici cilin
  • tree kernel

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

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