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Volumn 3488 LNAI, Issue , 2005, Pages 332-341

Discovering partial periodic sequential association rules with time lag in multiple sequences for prediction

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DATA MINING; DATA STRUCTURES; DATABASE SYSTEMS;

EID: 26944451649     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11425274_35     Document Type: Conference Paper
Times cited : (20)

References (10)
  • 3
    • 0032627945 scopus 로고    scopus 로고
    • Efficient mining of partial periodic patterns in time series database
    • Sydney, Australia. IEEE Computer Society
    • J. Han, G. Dong, and Y. Yin. Efficient mining of partial periodic patterns in time series database. In Fifteenth International Conference on Data Engineering, pages 106-115, Sydney, Australia, 1999. IEEE Computer Society.
    • (1999) Fifteenth International Conference on Data Engineering , pp. 106-115
    • Han, J.1    Dong, G.2    Yin, Y.3
  • 5
    • 0037986782 scopus 로고    scopus 로고
    • Discovering representative episodal association rules from event sequences using frequent closed episode sets and event constraints
    • San Jose, CA, November 29 - December 2
    • S. Harms, J. Deogun, J. Saquer, and T. Tadesse. Discovering representative episodal association rules from event sequences using frequent closed episode sets and event constraints. In Proceedings of the 2001 IEEE International Conference on Data Mining, pages 603-606, San Jose, CA, November 29 - December 2 2001.
    • (2001) Proceedings of the 2001 IEEE International Conference on Data Mining , pp. 603-606
    • Harms, S.1    Deogun, J.2    Saquer, J.3    Tadesse, T.4
  • 7
    • 0041454634 scopus 로고    scopus 로고
    • Discovering calendar-based temporal association rules
    • Yingjiu Li, Peng Ning, Xiaoyang Sean Wang, and Sushil Jajodia. Discovering calendar-based temporal association rules. In TIME, pages 111-118, 2001.
    • (2001) TIME , pp. 111-118
    • Li, Y.1    Ning, P.2    Wang, X.S.3    Jajodia, S.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.