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Volumn , Issue , 2005, Pages 562-567

Parallel mining of closed sequential patterns

Author keywords

Load balancing; Parallel algorithms; Sampling

Indexed keywords

DATA STORAGE EQUIPMENT; DISTRIBUTED COMPUTER SYSTEMS; INFORMATION ANALYSIS; PARALLEL PROCESSING SYSTEMS; PROBLEM SOLVING; SAMPLING;

EID: 32344453032     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1081870.1081937     Document Type: Conference Paper
Times cited : (74)

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    • Mining frequent patterns by pattern-growth: Methodology and implications
    • J. Han and J. Pei. Mining frequent patterns by pattern-growth: methodology and implications. SIGKDD Explor. Newsl., 2(2):14-20, 2000.
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    • Han, J.1    Pei, J.2
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    • Freespan: Frequent pattern-projected sequential pattern mining
    • ACM Press
    • J. Han, J. Pei, B. Mortazavi-Asl, Q. Chen, U. Dayal, and M.-C. Hsu. Freespan: frequent pattern-projected sequential pattern mining. In KDD'00, pages 355-359. ACM Press.
    • KDD'00 , pp. 355-359
    • Han, J.1    Pei, J.2    Mortazavi-Asl, B.3    Chen, Q.4    Dayal, U.5    Hsu, M.-C.6
  • 7
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    • PrefixSpan mining sequential patterns efficiently by prefix projected pattern growth
    • J. Pei, J. Han, B. Mortazavi-Asl, H. Pinto, Q. Chen, U. Dayal, and M.-C. Hsu. PrefixSpan mining sequential patterns efficiently by prefix projected pattern growth. In ICDE'01, pages 215-226.
    • ICDE'01 , pp. 215-226
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  • 8
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    • Mining sequential patterns: Generalizations and performance improvements
    • P. M. G. Apers, M. Bouzeghoub, and G. Gardarin, editors, Springer-Verlag
    • R. Srikant and R. Agrawal. Mining sequential patterns: Generalizations and performance improvements. In P. M. G. Apers, M. Bouzeghoub, and G. Gardarin, editors, Proc. 5th Int. Conf. Extending Database Technology, EDBT, volume 1057, pages 3-17. Springer-Verlag.
    • Proc. 5th Int. Conf. Extending Database Technology, EDBT , vol.1057 , pp. 3-17
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  • 9
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    • BIDE efficient mining of frequent closed sequences
    • J. Wang and J. Han. BIDE efficient mining of frequent closed sequences. In ICDE'04, pages 79-91.
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  • 10
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    • Clospan: Mining closed sequential patterns in large datasets
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    • Parallel sequence mining on shared-memory machines
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.