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Volumn , Issue , 2010, Pages 35-48

A sliding windows based dual support framework for discovering emerging trends from temporal data

Author keywords

[No Author keywords available]

Indexed keywords

INTELLIGENT SYSTEMS; LARGE DATASET;

EID: 84857363570     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-1-84882-983-1_3     Document Type: Conference Paper
Times cited : (6)

References (21)
  • 2
    • 56349132360 scopus 로고    scopus 로고
    • Mining frequent itemsets over data streams using efficient window sliding techniques
    • Li, H. F. & Lee, S. Y., 2009. Mining frequent itemsets over data streams using efficient window sliding techniques. Expert Systems with Applications, 36(2P1), 1466-1477.
    • (2009) Expert Systems with Applications , vol.36 , Issue.2 , pp. 1466-1477
    • Li, H.F.1    Lee, S.Y.2
  • 3
    • 0042850501 scopus 로고    scopus 로고
    • Progressive partition miner: An efficient algorithm for mining general temporal association rules
    • Lee, C. H., Chen, M. S. & Lin, C. R., 2003. Progressive partition miner: An efficient algorithm for mining general temporal association rules. IEEE Transactions on Knowledge and Data Engineering, 1004-1017.
    • (2003) IEEE Transactions on Knowledge and Data Engineering , pp. 1004-1017
    • Lee, C.H.1    Chen, M.S.2    Lin, C.R.3
  • 4
    • 3142639461 scopus 로고    scopus 로고
    • A sliding window method for finding recently frequent itemsets over online data streams
    • Chang, J. H. & Lee, W. S., 2004. A sliding window method for finding recently frequent itemsets over online data streams. Journal of Information Science and Engineering, 20(4), 753-762.
    • (2004) Journal of Information Science and Engineering , vol.20 , Issue.4 , pp. 753-762
    • Chang, J.H.1    Lee, W.S.2
  • 5
    • 33644920942 scopus 로고    scopus 로고
    • Research issues in data stream association rule mining
    • Jiang, N., 2006. Research issues in data stream association rule mining. ACM Sigmod Record, 35(1), 14-19.
    • (2006) ACM Sigmod Record , vol.35 , Issue.1 , pp. 14-19
    • Jiang, N.1
  • 17
    • 33645587779 scopus 로고    scopus 로고
    • Mining the strongest emerging patterns characterizing patients affected by diseases due to atherosclerosis
    • Cremilleux, B., Soulet, A. & Rioult, F., 2003. Mining the strongest emerging patterns characterizing patients affected by diseases due to atherosclerosis. In proceedings of the workshop Discovery Challenge, PKDD'03. 59-70.
    • (2003) Proceedings of the Workshop Discovery Challenge, PKDD'03 , pp. 59-70
    • Cremilleux, B.1    Soulet, A.2    Rioult, F.3
  • 19
    • 0032091573 scopus 로고    scopus 로고
    • Efficiently mining long patterns from databases
    • Bayardo Jr, R. J., 1998. Efficiently mining long patterns from databases. ACM SIGMOD Record, 27(2), 85-93.
    • (1998) ACM SIGMOD Record , vol.27 , Issue.2 , pp. 85-93
    • Bayardo Jr., R.J.1
  • 20
    • 0041562664 scopus 로고    scopus 로고
    • Programmable stream processors
    • Kapasi, U. J. et al., 2003. Programmable stream processors. Computer, 54-62.
    • (2003) Computer , pp. 54-62
    • Kapasi, U.J.1
  • 21
    • 84899332236 scopus 로고    scopus 로고
    • Effective mining of weighted fuzzy association rules, rare association rule mining and knowledge discovery: Technologies for infrequent and critical event detection, advances in data warehousing and mining (adwm) book Series
    • M. Sulaiman Khan, Muyeba, M. & Coenen, F., 2009. Effective Mining of Weighted Fuzzy Association Rules, Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection, Advances in Data Warehousing and Mining (ADWM) Book Series, IGI Global. ISBN: 978-1-60566-754-6, 47-64.
    • (2009) IGI Global ISBN: 978-1-60566-754-6 , pp. 47-64
    • Sulaiman Khan, M.1    Muyeba, M.2    Coenen, F.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.