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Volumn , Issue , 2006, Pages 667-674

URES: An unsupervised web relation extraction system

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; INFORMATION RETRIEVAL; INFORMATION RETRIEVAL SYSTEMS; MACHINE LEARNING; NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 38349050656     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (27)

References (21)
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    • Bikel, D. M., S. Miller, et al. (1997). Nymble: a high-performance learning name-finder. Proceedings of ANLP-97: 194-201.
    • (1997) Proceedings of ANLP-97 , pp. 194-201
    • Bikel, D. M.1    Miller, S.2
  • 3
    • 0003146263 scopus 로고    scopus 로고
    • Extracting Patterns and Relations from the World Wide Web
    • Brin, S. (1998). Extracting Patterns and Relations from the World Wide Web. WebDB Workshop, EDBT '98.
    • (1998) WebDB Workshop, EDBT '98
    • Brin, S.1
  • 5
    • 70349246101 scopus 로고
    • Evaluating Message Understanding Systems: An Analysis of the Third Message Understanding Conference (MUC-3)
    • Chinchor, N., L. Hirschman, et al. (1994). "Evaluating Message Understanding Systems: An Analysis of the Third Message Understanding Conference (MUC-3)." Computational Linguistics 3(19): 409-449.
    • (1994) Computational Linguistics , vol.3 , Issue.19 , pp. 409-449
    • Chinchor, N.1    Hirschman, L.2
  • 7
    • 17644423946 scopus 로고    scopus 로고
    • Unsupervised named-entity extraction from the Web: An experimental study
    • Etzioni, O., M. Cafarella, et al. (2005). "Unsupervised named-entity extraction from the Web: An experimental study." Artificial Intelligence.
    • (2005) Artificial Intelligence
    • Etzioni, O.1    Cafarella, M.2
  • 10
    • 0000747663 scopus 로고    scopus 로고
    • Maximum Entropy Markov Models for Information Extraction and Segmentation
    • Morgan Kaufmann, San Francisco, CA
    • McCallum, A., D. Freitag, et al. (2000). Maximum Entropy Markov Models for Information Extraction and Segmentation. Proc. 17th International Conf. on Machine Learning, Morgan Kaufmann, San Francisco, CA: 591-598.
    • (2000) Proc. 17th International Conf. on Machine Learning , pp. 591-598
    • McCallum, A.1    Freitag, D.2
  • 12
    • 84976702763 scopus 로고
    • WordNet: A lexical database for English
    • Miller, G. A. (1995). "WordNet: A lexical database for English." CACM 38(11): 39-41.
    • (1995) CACM , vol.38 , Issue.11 , pp. 39-41
    • Miller, G. A.1
  • 14
    • 0030352390 scopus 로고    scopus 로고
    • Automatically Generating Extraction Patterns from Untagged Text
    • Riloff, E. (1996). Automatically Generating Extraction Patterns from Untagged Text. AAAI/IAAI, Vol. 2: 1044-1049.
    • (1996) AAAI/IAAI , vol.2 , pp. 1044-1049
    • Riloff, E.1
  • 16
    • 18744406038 scopus 로고    scopus 로고
    • TEG: a hybrid approach to information extraction
    • Arlington, VA
    • Rosenfeld, B., R. Feldman, et al. (2004). TEG: a hybrid approach to information extraction. CIKM 2004, Arlington, VA.
    • (2004) CIKM 2004
    • Rosenfeld, B.1    Feldman, R.2
  • 17
    • 0032624184 scopus 로고    scopus 로고
    • Learning Information Extraction Rules for Semi-Structured and Free Text
    • Soderland, S. (1999). "Learning Information Extraction Rules for Semi-Structured and Free Text." Machine Learning 34(1-3): 233-272.
    • (1999) Machine Learning , vol.34 , Issue.1-3 , pp. 233-272
    • Soderland, S.1
  • 20
    • 0742306576 scopus 로고    scopus 로고
    • Background and overview for kdd cup 2002 task 1: Information extraction from biomedical articles
    • Yeh, A. and L. Hirschman (2002). "Background and overview for kdd cup 2002 task 1: Information extraction from biomedical articles." KDD Ex-plorarions 4(2): 87-89.
    • (2002) KDD Ex-plorarions , vol.4 , Issue.2 , pp. 87-89
    • Yeh, A.1    Hirschman, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.