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Volumn 1, Issue , 2008, Pages 293-298

Online data stream mining of recent frequent itemsets based on sliding window model

Author keywords

Data mining; Online data stream; Sliding windows

Indexed keywords

CONTROL THEORY; CYBERNETICS; DECODING; INFORMATION MANAGEMENT; KNOWLEDGE BASED SYSTEMS; KNOWLEDGE MANAGEMENT; LEARNING SYSTEMS; MINING; ROBOT LEARNING; WINDOWS;

EID: 57849094489     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLC.2008.4620420     Document Type: Conference Paper
Times cited : (2)

References (11)
  • 2
    • 33644920942 scopus 로고    scopus 로고
    • Research Issues in Data Stream Association Rule Mining
    • Mar
    • N. Jiang, and L. Gruenwald. Research Issues in Data Stream Association Rule Mining. In SIGMOD Record, Vol. 35, No. 1, Mar. 2006.
    • (2006) SIGMOD Record , vol.35 , Issue.1
    • Jiang, N.1    Gruenwald, L.2
  • 5
    • 3042644650 scopus 로고    scopus 로고
    • Decaying Obsolete Information in Finding Recent Frequent Itemsets over Data Stream
    • June
    • J. Chang and W. Lee. Decaying Obsolete Information in Finding Recent Frequent Itemsets over Data Stream. IEICE Transaction on Information and Systems, Vol. E87-D, No. 6, June, 2004.
    • (2004) IEICE Transaction on Information and Systems , vol.E87-D , Issue.6
    • Chang, J.1    Lee, W.2
  • 10
    • 3142639461 scopus 로고    scopus 로고
    • J. Chang and W. Lee. A Sliding Window Method for Finding Recently Frequent Itemsets over Online Data Streams. Journal of Information Science and Engineering, 20, No. 4, July, 2004.
    • J. Chang and W. Lee. A Sliding Window Method for Finding Recently Frequent Itemsets over Online Data Streams. Journal of Information Science and Engineering, Vol. 20, No. 4, July, 2004.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.