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Volumn , Issue , 2009, Pages 1521-1524

Mining frequent itemsets in time-varying data streams

Author keywords

Data stream; Frequent itemset

Indexed keywords

ACCURACY RATE; ARRIVAL RATES; DATA STREAM; FREQUENT ITEMSET; FREQUENT ITEMSETS; MINING FREQUENT ITEMSETS; REAL-WORLD APPLICATION; TIME-VARYING DATA;

EID: 74549172516     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1645953.1646161     Document Type: Conference Paper
Times cited : (7)

References (7)
  • 2
    • 3142639461 scopus 로고    scopus 로고
    • A sliding window method for finding recently frequent itemsets over online data streams
    • J. Chang and W. Lee. A sliding window method for finding recently frequent itemsets over online data streams. Journal of Information Science and Engineering, pages 753-762, 2004.
    • (2004) Journal of Information Science and Engineering , pp. 753-762
    • Chang, J.1    Lee, W.2
  • 3
    • 19544377965 scopus 로고    scopus 로고
    • Moment: Maintaining closed frequent itemsets over a stream sliding window
    • Y. Chi, H. Wang, P. Yu, and R. Muntz. Moment: Maintaining closed frequent itemsets over a stream sliding window. In Proc. 2004 IEEE Int. Conf. on Data Mining, pages 59-66, 2004.
    • (2004) Proc. 2004 IEEE Int. Conf. on Data Mining , pp. 59-66
    • Chi, Y.1    Wang, H.2    Yu, P.3    Muntz, R.4
  • 5
    • 33644920942 scopus 로고    scopus 로고
    • Research issues in data stream association rule mining
    • N. Jiang and L. Gruenwald. Research issues in data stream association rule mining. ACM SIGMOD Record, (1):14-19, 2006.
    • (2006) ACM SIGMOD Record , vol.1 , pp. 14-19
    • Jiang, N.1    Gruenwald, L.2
  • 6
    • 74549163486 scopus 로고    scopus 로고
    • Manku and Motwani. Approximate frequency counts over data streams. In Proc. 28th Int. Conf. on Very Large Data Bases, pages 346-357, 2002.
    • Manku and Motwani. Approximate frequency counts over data streams. In Proc. 28th Int. Conf. on Very Large Data Bases, pages 346-357, 2002.
  • 7
    • 79953236929 scopus 로고    scopus 로고
    • False positive or false negative: Mining frequent itemsets from high speed transactional data streams
    • J. Yu, Z. Chong, H. Lu, and A. Zhou. False positive or false negative: Mining frequent itemsets from high speed transactional data streams. In Proc. 30th Int. Conf. on Very Large Data Bases, pages 204-215, 2004.
    • (2004) Proc. 30th Int. Conf. on Very Large Data Bases , pp. 204-215
    • Yu, J.1    Chong, Z.2    Lu, H.3    Zhou, A.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.