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Volumn 68, Issue 1, 2009, Pages 49-67

An active learning framework for semi-supervised document clustering with language modeling

Author keywords

Active learning; Document clustering; Language modeling; Semi supervised

Indexed keywords

CLUSTER ANALYSIS; CLUSTERING ALGORITHMS; COMPUTATIONAL LINGUISTICS; FLOW OF SOLIDS; INDEXING (OF INFORMATION); INFORMATION RETRIEVAL; LINGUISTICS; PROBABILITY;

EID: 56249141770     PISSN: 0169023X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.datak.2008.08.008     Document Type: Article
Times cited : (48)

References (27)
  • 1
    • 1942517347 scopus 로고    scopus 로고
    • A. Bar-Hillel, T. Hertz, N. Shental, D. Weinshall, Learning distance functions using equivalence relations, in: Proceedings of the 12th International Conference on Machine Learning, 2003, pp. 11-18.
    • A. Bar-Hillel, T. Hertz, N. Shental, D. Weinshall, Learning distance functions using equivalence relations, in: Proceedings of the 12th International Conference on Machine Learning, 2003, pp. 11-18.
  • 2
    • 56249115277 scopus 로고    scopus 로고
    • S. Basu, A. Banerjee, R.J. Mooney, Semi-supervised clustering by seeding, in: Proceedings of the 19th International conference on Machine Learning, 2002, pp. 27-34.
    • S. Basu, A. Banerjee, R.J. Mooney, Semi-supervised clustering by seeding, in: Proceedings of the 19th International conference on Machine Learning, 2002, pp. 27-34.
  • 3
    • 2942534529 scopus 로고    scopus 로고
    • S. Basu, A. Banerjee, R.J. Mooney. Active semi-supervision for pairwise constrained clustering, in: Proceedings of the SIAM International Conference on Data Mining, 2004, pp. 333-344.
    • S. Basu, A. Banerjee, R.J. Mooney. Active semi-supervision for pairwise constrained clustering, in: Proceedings of the SIAM International Conference on Data Mining, 2004, pp. 333-344.
  • 4
    • 12244300524 scopus 로고    scopus 로고
    • S. Basu, M. Bilenko, R.J. Mooney, A probabilistic framework for semi-supervised clustering, in: Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004, pp. 59-68.
    • S. Basu, M. Bilenko, R.J. Mooney, A probabilistic framework for semi-supervised clustering, in: Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004, pp. 59-68.
  • 5
    • 14344264451 scopus 로고    scopus 로고
    • M. Bilenko, S. Basu, R.J. Mooney, Integrating constraints and metric learning in semi-supervised clustering, in: Proceedings of the International Conference on Machine Learning, 2004, pp. 81-88.
    • M. Bilenko, S. Basu, R.J. Mooney, Integrating constraints and metric learning in semi-supervised clustering, in: Proceedings of the International Conference on Machine Learning, 2004, pp. 81-88.
  • 7
    • 33646084850 scopus 로고    scopus 로고
    • Locally linear metric adaptation for semi-supervised clustering and image retrieval
    • Chang H., and Yeung D.Y. Locally linear metric adaptation for semi-supervised clustering and image retrieval. Pattern Recognition 39 7 (2006) 1253-1264
    • (2006) Pattern Recognition , vol.39 , Issue.7 , pp. 1253-1264
    • Chang, H.1    Yeung, D.Y.2
  • 8
    • 56249091818 scopus 로고    scopus 로고
    • D. Cohn, R. Caruana, A. McCallum, Semi-supervised clustering with user feedback, Technical Report TR2003-1892, Cornell University, 2003.
    • D. Cohn, R. Caruana, A. McCallum, Semi-supervised clustering with user feedback, Technical Report TR2003-1892, Cornell University, 2003.
  • 10
    • 84880095768 scopus 로고    scopus 로고
    • I. Davidson, S. Ravi, Clustering with constraints: feasibility issues and the k-means algorithm, in: Proceedings of the SIAM International Conference on Data Mining, 2005, pp. 138-149.
    • I. Davidson, S. Ravi, Clustering with constraints: feasibility issues and the k-means algorithm, in: Proceedings of the SIAM International Conference on Data Mining, 2005, pp. 138-149.
  • 11
    • 0034824884 scopus 로고    scopus 로고
    • Concept decompositions for large sparse text data using clustering
    • Dhillon I.S., and Modha D.S. Concept decompositions for large sparse text data using clustering. Machine Learning 42 1 (2001) 143-175
    • (2001) Machine Learning , vol.42 , Issue.1 , pp. 143-175
    • Dhillon, I.S.1    Modha, D.S.2
  • 12
    • 33751384621 scopus 로고    scopus 로고
    • R. Huang, Z. Zhang, W. Lam, Text clustering with limited user feedback under local metric learning, in: Proceedings of Asia Information Retrieval Symposium (AIRS), 2006, pp. 132-144.
    • R. Huang, Z. Zhang, W. Lam, Text clustering with limited user feedback under local metric learning, in: Proceedings of Asia Information Retrieval Symposium (AIRS), 2006, pp. 132-144.
  • 13
    • 56249111008 scopus 로고    scopus 로고
    • D. Klein, S.D. Kamvar, C. Manning, From instance-level constraints to space-level constraints: making the most of prior knowledge in data clustering, in: Proceedings of the 19th International Conference on Machine Learning, 2002, pp. 307-314.
    • D. Klein, S.D. Kamvar, C. Manning, From instance-level constraints to space-level constraints: making the most of prior knowledge in data clustering, in: Proceedings of the 19th International Conference on Machine Learning, 2002, pp. 307-314.
  • 14
    • 34548562145 scopus 로고    scopus 로고
    • N. Kumar, K. Kummamuru, D. Paranjpe, Semi-supervised clustering with metric learning using relative comparisons, in: Proceedings of 5th IEEE International Conference on Data Mining, 2005, pp. 693-696.
    • N. Kumar, K. Kummamuru, D. Paranjpe, Semi-supervised clustering with metric learning using relative comparisons, in: Proceedings of 5th IEEE International Conference on Data Mining, 2005, pp. 693-696.
  • 15
    • 36049012687 scopus 로고    scopus 로고
    • Text document clustering based on frequent word meaning sequences
    • Li Y., Chung S.M., and Holt J.D. Text document clustering based on frequent word meaning sequences. Data and Knowledge Engineering 64 (2008) 381-404
    • (2008) Data and Knowledge Engineering , vol.64 , pp. 381-404
    • Li, Y.1    Chung, S.M.2    Holt, J.D.3
  • 16
    • 56249097308 scopus 로고    scopus 로고
    • National Institute of Standards, The 2002 Topic Detection and Tracking Task Definition and Evaluation Plan, 2002. .
    • National Institute of Standards, The 2002 Topic Detection and Tracking Task Definition and Evaluation Plan, 2002. .
  • 17
    • 56249092849 scopus 로고    scopus 로고
    • K. Nigam, A. McCallum, Pool-based active learning for text classification, in: Workshop on Learning from Text and the Web, Conference on Automated Learning and Discovery, 1998.
    • K. Nigam, A. McCallum, Pool-based active learning for text classification, in: Workshop on Learning from Text and the Web, Conference on Automated Learning and Discovery, 1998.
  • 18
    • 0032268440 scopus 로고    scopus 로고
    • J. Pone, W.B. Croft, A language modeling approach to information retrieval, in: Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 1998, pp. 275-281.
    • J. Pone, W.B. Croft, A language modeling approach to information retrieval, in: Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 1998, pp. 275-281.
  • 19
    • 84880733494 scopus 로고    scopus 로고
    • T. Rose, M. Stevenson, M. Whitehea, The reuters corpus volume 1- from yesterday's news to tomorrow's language resources, in: Proceedings of 3rd International Conference on Language Resources and Evaluation, 2002, pp. 29-31.
    • T. Rose, M. Stevenson, M. Whitehea, The reuters corpus volume 1- from yesterday's news to tomorrow's language resources, in: Proceedings of 3rd International Conference on Language Resources and Evaluation, 2002, pp. 29-31.
  • 20
    • 56249123343 scopus 로고    scopus 로고
    • M. Steinback, G. Karypis, V. Kumar, A comparison of document clustering techniques, in: KDD Workshop on Text Mining, 2000.
    • M. Steinback, G. Karypis, V. Kumar, A comparison of document clustering techniques, in: KDD Workshop on Text Mining, 2000.
  • 21
    • 56249146388 scopus 로고    scopus 로고
    • A. Strehl, J. Ghosh, R. Mooney, Impact of similarity measures on web-page clustering, in: Workshop on Artificial Intelligence for Web Search (AAAI 2000), 2000, p. 58-64.
    • A. Strehl, J. Ghosh, R. Mooney, Impact of similarity measures on web-page clustering, in: Workshop on Artificial Intelligence for Web Search (AAAI 2000), 2000, p. 58-64.
  • 22
    • 56249141885 scopus 로고    scopus 로고
    • K. Wagstaff, C. Cardie, Clustering with instance-level constraints, in: Proceedings of the 17th International Conference on Machine Learning, 2000, pp. 1103-1110.
    • K. Wagstaff, C. Cardie, Clustering with instance-level constraints, in: Proceedings of the 17th International Conference on Machine Learning, 2000, pp. 1103-1110.
  • 23
    • 84879571292 scopus 로고    scopus 로고
    • Distance metric learning, with application to clustering with side-information
    • Xing E.P., Ng A.Y., Jordan M., and Russell S. Distance metric learning, with application to clustering with side-information. Advances in NIPS 15 (2003) 521-528
    • (2003) Advances in NIPS , vol.15 , pp. 521-528
    • Xing, E.P.1    Ng, A.Y.2    Jordan, M.3    Russell, S.4
  • 24
    • 33750297659 scopus 로고    scopus 로고
    • B. Yan, C. Domeniconi, Subspace metric ensembles for semi-supervised clustering of high dimensional data, in: Proceedings of the 17th European Conference on Machine Learning, 2006, pp. 509-520.
    • B. Yan, C. Domeniconi, Subspace metric ensembles for semi-supervised clustering of high dimensional data, in: Proceedings of the 17th European Conference on Machine Learning, 2006, pp. 509-520.
  • 25
    • 3042824043 scopus 로고    scopus 로고
    • A study of smoothing methods for language models applied to information retrieval
    • Zhai C., and Lafferty J. A study of smoothing methods for language models applied to information retrieval. ACM Transactions on Information Systems 22 (2004) 179-214
    • (2004) ACM Transactions on Information Systems , vol.22 , pp. 179-214
    • Zhai, C.1    Lafferty, J.2
  • 26
    • 24044537630 scopus 로고    scopus 로고
    • Hierarchical clustering algorithms for document datasets
    • Zhao Y., and Karypis G. Hierarchical clustering algorithms for document datasets. Data Mining and Knowledge Discovery 10 (2005) 141-168
    • (2005) Data Mining and Knowledge Discovery , vol.10 , pp. 141-168
    • Zhao, Y.1    Karypis, G.2
  • 27
    • 33749013037 scopus 로고    scopus 로고
    • Semi-supervised model-based document clustering: a comparative study
    • Zhong S. Semi-supervised model-based document clustering: a comparative study. Machine Learning 65 (2006) 3-29
    • (2006) Machine Learning , vol.65 , pp. 3-29
    • Zhong, S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.