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Volumn 3056, Issue , 2004, Pages 441-451

Efficient pattern-growth methods for frequent tree pattern mining

Author keywords

[No Author keywords available]

Indexed keywords

CHOPPERS (CIRCUITS); DIGITAL LIBRARIES; FORESTRY; ALGORITHMS; DATA MINING; DATABASE SYSTEMS; ELECTRONIC COMMERCE; RESEARCH AND DEVELOPMENT MANAGEMENT; TREES (MATHEMATICS);

EID: 7444249756     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-24775-3_54     Document Type: Conference Paper
Times cited : (54)

References (13)
  • 1
    • 0141764033 scopus 로고    scopus 로고
    • A tree projection algorithm for generation of frequent item sets
    • R. C. Agarwal, et al. A tree projection algorithm for generation of frequent item sets. J. of Parallel and Distributed Computing, 61(3):350–371, 2001.
    • (2001) J. Of Parallel and Distributed Computing , vol.61 , Issue.3 , pp. 350-371
    • Agarwal, R.C.1
  • 2
    • 4544334171 scopus 로고    scopus 로고
    • Efficient substructure discovery from large semi-structured data
    • Arlington, VA
    • T. Asai, et al. Efficient substructure discovery from large semi-structured data. In Proc. 2002 SIAM Int. Conf. Data Mining, Arlington, VA.
    • Proc. 2002 SIAM Int. Conf. Data Mining
    • Asai, T.1
  • 3
    • 0027652468 scopus 로고
    • Substructure discovery using minimal description length and background knowledge
    • D. Cook and L. Holder. Substructure discovery using minimal description length and background knowledge. J. of Artificial Intelligence Research, 1:231–255, 1994.
    • (1994) J. Of Artificial Intelligence Research , vol.1 , pp. 231-255
    • Cook, D.1    Holder, L.2
  • 4
    • 0002037484 scopus 로고    scopus 로고
    • Finding frequent substructures in chemical compounds
    • New York, NY
    • L. Dehaspe, et al. Finding frequent substructures in chemical compounds. In KDD’98, New York, NY.
    • KDD’98
    • Dehaspe, L.1
  • 5
    • 0039253846 scopus 로고    scopus 로고
    • Mining frequent patterns without candidate generation
    • Dallas, TX
    • J. Han, et al. Mining frequent patterns without candidate generation. In SIGMOD’ 00, Dallas, TX.
    • SIGMOD’ 00
    • Han, J.1
  • 6
    • 78149312583 scopus 로고    scopus 로고
    • Frequent subgraph discovery
    • San Jose, CA
    • M. Kuramochi and G. Karypis. Frequent subgraph discovery. In ICDM’01, San Jose, CA.
    • ICDM’01
    • Kuramochi, M.1    Karypis, G.2
  • 7
    • 33645630820 scopus 로고    scopus 로고
    • Discovery of frequent tree structured patterns in semistructured web documents
    • Hong Kong, China
    • T. Miyahara, et al. Discovery of frequent tree structured patterns in semistructured web documents. In PAKDD’01, Hong Kong, China.
    • PAKDD’01
    • Miyahara, T.1
  • 9
    • 0035016443 scopus 로고    scopus 로고
    • PrefixSpan: Mining sequential patterns efficiently by prefix-projected pattern growth
    • Heidelberg, Germany
    • J. Pei, et al. PrefixSpan: Mining sequential patterns efficiently by prefix-projected pattern growth. In ICDE’01, Heidelberg, Germany.
    • ICDE’01
    • Pei, J.1
  • 11
    • 84943171773 scopus 로고    scopus 로고
    • Automated discovery of active motifs in multiple RNA secondary structures
    • Portland, Oregon
    • J.T.L. Wang, et al. Automated discovery of active motifs in multiple RNA secondary structures. In KDD’96, Portland, Oregon.
    • KDD’96
    • Wang, J.1
  • 12
    • 0002334869 scopus 로고    scopus 로고
    • Schema discovery for semistructured data
    • Newport Beach, CA
    • K. Wang and H. Liu. Schema discovery for semistructured data. In KDD’97, Newport Beach, CA.
    • KDD’97
    • Wang, K.1    Liu, H.2
  • 13
    • 33744829786 scopus 로고    scopus 로고
    • Efficiently mining frequent trees in a forest
    • Alberta, Canada
    • M.J. Zaki. Efficiently mining frequent trees in a forest. In KDD’02, Edmonton, Alberta, Canada.
    • KDD’02, Edmonton
    • Zaki, M.J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.