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Volumn , Issue , 2011, Pages 582-590

Direct local pattern sampling by efficient two-step random procedures

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING;

EID: 80052653056     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2020408.2020500     Document Type: Conference Paper
Times cited : (76)

References (28)
  • 2
    • 84865096110 scopus 로고    scopus 로고
    • Output space sampling for graph patterns
    • M. Al Hasan and M. J. Zaki. Output space sampling for graph patterns. PVLDB, 2(1):730-741, 2009.
    • (2009) PVLDB , vol.2 , Issue.1 , pp. 730-741
    • Hasan, M.A.1    Zaki, M.J.2
  • 3
    • 23044527560 scopus 로고    scopus 로고
    • Detecting group differences: Mining contrast sets
    • S. D. Bay and M. J. Pazzani. Detecting group differences: Mining contrast sets. Data Min. Knowl. Discov., 5(3):213-246, 2001.
    • (2001) Data Min. Knowl. Discov. , vol.5 , Issue.3 , pp. 213-246
    • Bay, S.D.1    Pazzani, M.J.2
  • 5
    • 34247149033 scopus 로고    scopus 로고
    • Soft constraint based pattern mining
    • DOI 10.1016/j.datak.2006.07.008, PII S0169023X06001418
    • S. Bistarelli and F. Bonchi. Soft constraint based pattern mining. Data and Knowl. Engineering, 62(1):118-137, 2007. (Pubitemid 46603196)
    • (2007) Data and Knowledge Engineering , vol.62 , Issue.1 , pp. 118-137
    • Bistarelli, S.1    Bonchi, F.2
  • 7
    • 70349902233 scopus 로고    scopus 로고
    • Approximating the number of frequent sets in dense data
    • M. Boley and H. Grosskreutz. Approximating the number of frequent sets in dense data. Knowl. Inf. Syst., 21(1):65-89, 2009.
    • (2009) Knowl. Inf. Syst. , vol.21 , Issue.1 , pp. 65-89
    • Boley, M.1    Grosskreutz, H.2
  • 8
    • 70350719970 scopus 로고    scopus 로고
    • Origami A novel and e-ective approach for mining representative orthogonal graph patterns
    • V. Chaoji, M. A. Hasan, S. Salem, J. Besson, and M. J. Zaki. Origami: A novel and e-ective approach for mining representative orthogonal graph patterns. Stat. Anal. Data Min., 1(2):67-84, 2008.
    • (2008) Stat. Anal. Data Min. , vol.1 , Issue.2 , pp. 67-84
    • Chaoji, V.1    Hasan, M.A.2    Salem, S.3    Besson, J.4    Zaki, M.J.5
  • 9
    • 34548741255 scopus 로고    scopus 로고
    • Discriminative frequent pattern analysis for effective classification
    • DOI 10.1109/ICDE.2007.367917, 4221720, 23rd International Conference on Data Engineering, ICDE 2007
    • H. Cheng, X. Yan, J. Han, and C.-W. Hsu. Discriminative frequent pattern analysis for effective classification. In Proc. 23rd Int. Conf. on Data Engineering (ICDE 2007), pp. 716-725, 2007. (Pubitemid 47422075)
    • (2007) Proceedings - International Conference on Data Engineering , pp. 716-725
    • Cheng, H.1    Yan, X.2    Han, J.3    Hsu, C.-W.4
  • 11
    • 29644438050 scopus 로고    scopus 로고
    • Statistical comparisons of classifiers over multiple data sets
    • J. Demsar. Statistical comparisons of classifiers over multiple data sets. J. of Mach. Learn. Res., 7:1-30, 2006. (Pubitemid 43022939)
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 1-30
    • Demsar, J.1
  • 18
    • 84948968508 scopus 로고    scopus 로고
    • Discovering all most specific sentences by randomized algorithms
    • Database Theory - ICDT '97
    • D. Gunopulos, H. Mannila, and S. Saluja. Discovering all most specific sentences by randomized algorithms. In Proc. 6th Int. Conf. of Database Theory (ICDT'97), vol. 1186 of LNCS, pp. 215-229, 1997. (Pubitemid 127013755)
    • (1997) Lecture Notes in Computer Science , Issue.1186 , pp. 215-229
    • Gunopulos, D.1    Mannila, H.2    Saluja, S.3
  • 19
    • 2442449952 scopus 로고    scopus 로고
    • Mining frequent patterns without candidate generation: A frequent-pattern tree approach
    • DOI 10.1023/B:DAMI.0000005258.31418.83
    • J. Han, J. Pei, Y. Yin, and R. Mao. Mining frequent patterns without candidate generation: A frequent-pattern tree approach. Data Min. Knowl. Discov., 8(1):53-87, 2004. (Pubitemid 39019971)
    • (2004) Data Mining and Knowledge Discovery , vol.8 , Issue.1 , pp. 53-87
    • Han, J.1    Pei, J.2    Yin, Y.3    Mao, R.4
  • 20
  • 21
    • 0001202403 scopus 로고
    • Monte-carlo approximation algorithms for enumeration problems
    • R. M. Karp, M. Luby, and N. Madras. Monte-carlo approximation algorithms for enumeration problems. J. Algorithms, 10(3):429-448, 1989.
    • (1989) J. Algorithms , vol.10 , Issue.3 , pp. 429-448
    • Karp, R.M.1    Luby, M.2    Madras, N.3
  • 25
    • 0141719772 scopus 로고    scopus 로고
    • Finding the most interesting patterns in a database quickly by using sequential sampling
    • T. Scheffer and S. Wrobel. Finding the most interesting patterns in a database quickly by using sequential sampling. J. of Mach. Learn. Res., 3:833-862, 2002.
    • (2002) J. of Mach. Learn. Res. , vol.3 , pp. 833-862
    • Scheffer, T.1    Wrobel, S.2
  • 27
    • 34548792706 scopus 로고    scopus 로고
    • An Algorithm for Multi-relational Discovery of Subgroups
    • Principles of Data Mining and Knowledge Discovery
    • S. Wrobel. An algorithm for multi-relational discovery of subgroups. In Proc. 1st Euro. Symp. on Principles of Data Mining and Knowl. Disc. (PKDD'97), vol. 1263 of LNCS, pp. 78-87. Springer, 1997. (Pubitemid 127097494)
    • (1997) Lecture Notes in Computer Science , Issue.1263 , pp. 78-87
    • Wrobel, S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.