A novel composite kernel approach to chinese entity relation extraction

Ji Zhang; You Ouyang; Wenjie Li; Yuexian Hou

doi:10.1007/978-3-642-00831-3_22

A novel composite kernel approach to chinese entity relation extraction

Ji Zhang, You Ouyang, Wenjie Li, Yuexian Hou

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

13 Citations (Scopus)

Abstract

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 language	English
Title of host publication	Computer Processing of Oriental Languages
Subtitle of host publication	Language Technology for the Knowledge-based Economy - 22nd International Conference, ICCPOL 2009, Proceedings
Pages	236-247
Number of pages	12
DOIs	https://doi.org/10.1007/978-3-642-00831-3_22
Publication status	Published - 9 Nov 2009
Event	22nd International Conference on Computer Processing of Oriental Languages, ICCPOL 2009 - , Hong Kong Duration: 26 Mar 2009 → 27 Mar 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5459 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Computer Processing of Oriental Languages, ICCPOL 2009
Country/Territory	Hong Kong
Period	26/03/09 → 27/03/09

Keywords

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

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

More information

10.1007/978-3-642-00831-3_22

Cite this

Zhang, J., Ouyang, Y., Li, W., & Hou, Y. (2009). A novel composite kernel approach to chinese entity relation extraction. In Computer Processing of Oriental Languages: Language Technology for the Knowledge-based Economy - 22nd International Conference, ICCPOL 2009, Proceedings (pp. 236-247). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5459 LNAI). https://doi.org/10.1007/978-3-642-00831-3_22

Zhang, Ji ; Ouyang, You ; Li, Wenjie et al. / A novel composite kernel approach to chinese entity relation extraction. Computer Processing of Oriental Languages: Language Technology for the Knowledge-based Economy - 22nd International Conference, ICCPOL 2009, Proceedings. 2009. pp. 236-247 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{af7050bba6c247c1bf02257673e44cee,

title = "A novel composite kernel approach to chinese entity relation extraction",

abstract = "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.",

keywords = "Composite Kernel, Entity Kernel, Kernel-based Chinese Relation Extraction, String Semantic Similarity Kernel",

author = "Ji Zhang and You Ouyang and Wenjie Li and Yuexian Hou",

year = "2009",

month = nov,

day = "9",

doi = "10.1007/978-3-642-00831-3_22",

language = "English",

isbn = "3642008305",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "236--247",

booktitle = "Computer Processing of Oriental Languages",

note = "22nd International Conference on Computer Processing of Oriental Languages, ICCPOL 2009 ; Conference date: 26-03-2009 Through 27-03-2009",

}

Zhang, J, Ouyang, Y, Li, W & Hou, Y 2009, A novel composite kernel approach to chinese entity relation extraction. in Computer Processing of Oriental Languages: Language Technology for the Knowledge-based Economy - 22nd International Conference, ICCPOL 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5459 LNAI, pp. 236-247, 22nd International Conference on Computer Processing of Oriental Languages, ICCPOL 2009, Hong Kong, 26/03/09. https://doi.org/10.1007/978-3-642-00831-3_22

A novel composite kernel approach to chinese entity relation extraction. / Zhang, Ji; Ouyang, You; Li, Wenjie et al.
Computer Processing of Oriental Languages: Language Technology for the Knowledge-based Economy - 22nd International Conference, ICCPOL 2009, Proceedings. 2009. p. 236-247 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5459 LNAI).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - A novel composite kernel approach to chinese entity relation extraction

AU - Zhang, Ji

AU - Ouyang, You

AU - Li, Wenjie

AU - Hou, Yuexian

PY - 2009/11/9

Y1 - 2009/11/9

N2 - 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.

AB - 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.

KW - Composite Kernel

KW - Entity Kernel

KW - Kernel-based Chinese Relation Extraction

KW - String Semantic Similarity Kernel

UR - http://www.scopus.com/inward/record.url?scp=70350637705&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-00831-3_22

DO - 10.1007/978-3-642-00831-3_22

M3 - Conference article published in proceeding or book

SN - 3642008305

SN - 9783642008306

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 236

EP - 247

BT - Computer Processing of Oriental Languages

T2 - 22nd International Conference on Computer Processing of Oriental Languages, ICCPOL 2009

Y2 - 26 March 2009 through 27 March 2009

ER -

Zhang J, Ouyang Y, Li W, Hou Y. A novel composite kernel approach to chinese entity relation extraction. In Computer Processing of Oriental Languages: Language Technology for the Knowledge-based Economy - 22nd International Conference, ICCPOL 2009, Proceedings. 2009. p. 236-247. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-00831-3_22

A novel composite kernel approach to chinese entity relation extraction

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

More information

Other files and links

Fingerprint

Cite this