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Volumn 43, Issue 4, 2007, Pages 969-982

Extracting relation information from text documents by exploring various types of knowledge

Author keywords

Feature based relation extraction; Information extraction; Knowledge exploration; Support vector machines

Indexed keywords

INFORMATION MANAGEMENT; INFORMATION RETRIEVAL; KNOWLEDGE BASED SYSTEMS; SEMANTICS; SUPPORT VECTOR MACHINES; SYNTACTICS;

EID: 33947183528     PISSN: 03064573     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ipm.2006.09.012     Document Type: Article
Times cited : (43)

References (18)
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    • Joachimi, T. (1998). Text categorization with support vector machines: Learning with many relevant features. ECML'1998:1370142, 21-23 April 1998, Chemnitz, Germany.
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    • Kambhatla, N. (2004). Combining lexical, syntactic and semantic features with maximum entropy models for extracting relations. ACL'2004(poster) (pp. 178-181), 21-26 July 2004, Barcelona, Spain.
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    • Zhang, M., Su, J., Wang, D. M., Zhou, G. D., & Tan, C. L. (2005). Discovering relations from a large raw corpus using tree similarity-based clustering. IJCNLP'2005, Lecture Notes in Computer Science (LNCS 3651) (pp. 378-389), 11-16 October 2005, Jeju Island, South Korea.
  • 17
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    • Zhao, S. B., & Grisman, R. (2005). Extracting relations with integrated information using kernel methods. ACL'2005 (pp. 419-426), 25-30 June 2005, Ann Arbor, USA.
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    • Zhou, G. D., Su, J., Zhang, J., & Zhang, M. (2005). Exploring various knowledge in relation extraction. ACL'2005 (pp. 427-434), 25-30 June 2005, Ann Arbor, USA.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.