메뉴 건너뛰기




Volumn 33, Issue 3, 2008, Pages 300-314

Mining relational data from text: From strictly supervised to weakly supervised learning

Author keywords

Active learning; Bootstrapping; Information extraction; Random subspace method; Relation classification; Support vector machines

Indexed keywords

DATA STRUCTURES; LEARNING ALGORITHMS; SUPERVISED LEARNING; SUPPORT VECTOR MACHINES;

EID: 38349097381     PISSN: 03064379     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.is.2007.10.002     Document Type: Article
Times cited : (13)

References (47)
  • 1
    • 38349151150 scopus 로고    scopus 로고
    • H. Cunningham, D. Maynard, K. Bontcheva, V. Tablan, GATE: A framework and graphical development environment for robust NLP tools and applications, in: Proceedings of the 40th Anniversary Meeting of the Association for Computational Linguistics, 2002.
  • 4
    • 38349161293 scopus 로고    scopus 로고
    • A. Culotta, J. Sorensen, Dependency tree kernels for relation extraction, in: ACL, 2004, pp. 423-429.
  • 6
    • 38349191296 scopus 로고    scopus 로고
    • B. Rosario, M. Hearst, Classifying semantic relations in bioscience text, in: Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics, 2004.
  • 8
    • 38349120677 scopus 로고    scopus 로고
    • S. Brin, Extracting patterns and relations from the world wide web, in: WebDB Workshop at sixth International Conference on Extending Database Technology, EDBT'98, 1998.
  • 9
    • 0033652943 scopus 로고    scopus 로고
    • E. Agichtein, L. Gravano, Snowball: Extracting relations from large plain-text collections, in: Proceedings of the Fifth ACM International Conference on Digital Libraries, 2000.
  • 10
    • 84880902141 scopus 로고    scopus 로고
    • M. Banko, M.J. Cafarella, S. Soderland, M. Broadhead, O. Etzioni, Open information extraction from the web, in: IJCAI, 2007, pp. 2670-2676.
  • 14
    • 84957069814 scopus 로고    scopus 로고
    • T. Joachims, Text categorization with support vector machines: learning with many relevant features, in: C. Nédellec, C. Rouveirol (Eds.), Proceedings of ECML-98, 10th European Conference on Machine Learning, vol. 1398, Chemnitz, DE, Springer Verlag, Heidelberg DE, 1998, pp. 137-142.
  • 15
    • 38349134465 scopus 로고    scopus 로고
    • T. Kudo, Y. Matsumoto, Chunking with support vector machines, in: Proceedings of NAACL, 2001, pp. 192-199.
  • 18
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman L. Bagging predictors. Mach. Learn. 24 2 (1996) 123-140
    • (1996) Mach. Learn. , vol.24 , Issue.2 , pp. 123-140
    • Breiman, L.1
  • 19
    • 0031211090 scopus 로고    scopus 로고
    • A decision-theoretic generalization of on-line learning and an application to boosting
    • Freund Y., and Schapire R.E. A decision-theoretic generalization of on-line learning and an application to boosting. J. Comput. System Sci. 55 1 (1997) 119-139
    • (1997) J. Comput. System Sci. , vol.55 , Issue.1 , pp. 119-139
    • Freund, Y.1    Schapire, R.E.2
  • 20
    • 38349151836 scopus 로고    scopus 로고
    • M. Banko, E. Brill, Scaling to very very large corpora for natural language disambiguation, in: Meeting of the Association for Computational Linguistics, 2001, pp. 26-33.
  • 21
    • 38349086328 scopus 로고    scopus 로고
    • V. Ng, C. Cardie, Weakly supervised natural language learning without redundant views, in: HLT-NAACL 2003: Proceedings of the Main Conference, 2003, pp. 173-180.
  • 22
    • 0032139235 scopus 로고    scopus 로고
    • The random subspace method for constructing decision forests
    • Ho T.K. The random subspace method for constructing decision forests. IEEE Trans. Pattern Anal. Mach. Intell. 20 8 (1998) 832-844
    • (1998) IEEE Trans. Pattern Anal. Mach. Intell. , vol.20 , Issue.8 , pp. 832-844
    • Ho, T.K.1
  • 23
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • Breiman L. Random forests. Mach. Learn. 45 1 (2001) 5-32
    • (2001) Mach. Learn. , vol.45 , Issue.1 , pp. 5-32
    • Breiman, L.1
  • 24
    • 0028424239 scopus 로고
    • Improving generalization with active learning
    • Cohn D., Atlas L., and Ladner R. Improving generalization with active learning. Mach. Learn. 15 2 (1994) 201-221
    • (1994) Mach. Learn. , vol.15 , Issue.2 , pp. 201-221
    • Cohn, D.1    Atlas, L.2    Ladner, R.3
  • 25
    • 38349186276 scopus 로고    scopus 로고
    • C.A. Thompson, M.E. Califf, R.J. Mooney, Active learning for natural language parsing and information extraction, in: Proceedings of 16th International Conference on Machine Learning, Morgan Kaufmann, San Francisco CA, 1999, pp. 406-414.
  • 26
    • 38349143020 scopus 로고    scopus 로고
    • D.D. Lewis, J. Catlett, Heterogeneous uncertainty sampling for supervised learning. in: W.W. Cohen, H. Hirsh (Eds.), Proceedings of ICML-94, 11th International Conference on Machine Learning, New Brunswick, US, Morgan Kaufmann Publishers, San Francisco, USA, 1994, pp. 148-156.
  • 27
    • 85013879626 scopus 로고    scopus 로고
    • D.D. Lewis, W.A. Gale, A sequential algorithm for training text classifiers, in: Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval, Springer-Verlag, New York, Inc., 1994, pp. 3-12.
  • 28
    • 0031209604 scopus 로고    scopus 로고
    • Selective sampling using the query by committee algorithm
    • Freund Y., Seung H.S., Shamir E., and Tishby N. Selective sampling using the query by committee algorithm. Mach. Learn. 28 2-3 (1997) 133-168
    • (1997) Mach. Learn. , vol.28 , Issue.2-3 , pp. 133-168
    • Freund, Y.1    Seung, H.S.2    Shamir, E.3    Tishby, N.4
  • 29
    • 0242445747 scopus 로고    scopus 로고
    • Committee-based sample selection for probabilistic classifiers
    • Argamon-Engelson S., and Dagan I. Committee-based sample selection for probabilistic classifiers. J. Artif. Intell. Res. 11 (1999) 335-360
    • (1999) J. Artif. Intell. Res. , vol.11 , pp. 335-360
    • Argamon-Engelson, S.1    Dagan, I.2
  • 30
    • 0042868698 scopus 로고    scopus 로고
    • Support vector machine active learning with applications to text classification
    • Tong S., and Koller D. Support vector machine active learning with applications to text classification. J. Mach. Learn. Res. 2 (2001) 45-66
    • (2001) J. Mach. Learn. Res. , vol.2 , pp. 45-66
    • Tong, S.1    Koller, D.2
  • 31
    • 0000012198 scopus 로고    scopus 로고
    • Selective sampling for example-based word sense disambiguation
    • Fujii A., Inui K., Tokunaga T., and Tanaka H. Selective sampling for example-based word sense disambiguation. Comput. Linguistics 24 4 (1998) 573-598
    • (1998) Comput. Linguistics , vol.24 , Issue.4 , pp. 573-598
    • Fujii, A.1    Inui, K.2    Tokunaga, T.3    Tanaka, H.4
  • 33
    • 38349120234 scopus 로고    scopus 로고
    • M. Sassano, An empirical study of active learning with support vector machines for japanese word segmentation, in: Proceedings of ACL-02, 40th Annual Meeting of the Association for Computational Linguistics, 2002.
  • 35
    • 38349171453 scopus 로고    scopus 로고
    • J. Baldridge, M. Osborne, Active learning for HPSG parse selection, in: Proceedings of the seventh Conference on Natural Language Learning, 2003.
  • 36
    • 38349184146 scopus 로고    scopus 로고
    • M. Tang, X. Luo, S. Roukos, Active learning for statistical natural language parsing, in: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL), 2002, pp. 120-127.
  • 37
    • 38349146415 scopus 로고    scopus 로고
    • X. Zhu, Semi-supervised learning literature survey. Technical Report 1530, Computer Sciences, University of Wisconsin-Madison. 〈http://www.cs.wisc.edu/∼jerryzhu/pub/ssl_survey.pdf〉.
  • 38
    • 38349153497 scopus 로고    scopus 로고
    • D. Yarowsky, Unsupervised word sense disambiguation rivaling supervised methods, in: Meeting of the Association for Computational Linguistics,1995, pp. 189-196.
  • 39
    • 18744410770 scopus 로고    scopus 로고
    • Understanding the Yarowsky algorithm
    • Abney S. Understanding the Yarowsky algorithm. Comput. Linguistics 30 3 (2004)
    • (2004) Comput. Linguistics , vol.30 , Issue.3
    • Abney, S.1
  • 41
    • 38349188108 scopus 로고    scopus 로고
    • M. Collins, Y. Singer, Unsupervised models for named entity classification, in: EMNLP/VLC-99, 1999.
  • 44
    • 38349163075 scopus 로고    scopus 로고
    • E. Charniak, A maximum-entropy-inspired parser, Technical Report CS-99-12, Computer Scicence Department, Brown University, 1999.
  • 45
    • 38349162515 scopus 로고    scopus 로고
    • C.-C. Chang, C.-J. Lin, LIBSVM: a library for support vector machines. Software available at, 〈 http://www.csie.ntu.edu.tw/∼cjlin/libsvm〉, 2001.
  • 46
    • 38349084939 scopus 로고    scopus 로고
    • S. Abney, Bootstrapping, in: Proceedings of ACL-02, 40th Annual Meeting of the Association for Computational Linguistics, 2002.
  • 47
    • 84898930761 scopus 로고    scopus 로고
    • Co-training and expansion: towards bridging theory and practice
    • Saul L.K., Weiss Y., and Bottou L. (Eds), MIT Press, Cambridge, MA
    • Balcan M.-F., Blum A., and Yang K. Co-training and expansion: towards bridging theory and practice. In: Saul L.K., Weiss Y., and Bottou L. (Eds). Advances in Neural Information Processing Systems vol. 17 (2005), MIT Press, Cambridge, MA 489-496
    • (2005) Advances in Neural Information Processing Systems , vol.17 , pp. 489-496
    • Balcan, M.-F.1    Blum, A.2    Yang, K.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.