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Volumn , Issue , 2010, Pages 1034-1038

Mining uncertain data for frequent itemsets that satisfy aggregate constraints

Author keywords

aggregate functions; constraints; data mining; frequent patterns; probabilistic databases

Indexed keywords

AGGREGATE CONSTRAINT; AGGREGATE FUNCTION; AGGREGATE FUNCTIONS; CANDIDATE GENERATION; FREQUENT ITEMSETS; FREQUENT PATTERNS; MINING PROCESS; PROBABILISTIC DATABASE; TRANSACTION DATABASE; TREE-BASED ALGORITHMS; UNCERTAIN DATAS; USER CONSTRAINTS; USER INTERESTS;

EID: 77954748923     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1774088.1774305     Document Type: Conference Paper
Times cited : (14)

References (29)
  • 1
    • 52649142649 scopus 로고    scopus 로고
    • A framework for clustering uncertain data streams
    • C.C. Aggarwal and P.S. Yu. A framework for clustering uncertain data streams. In Proc. IEEE ICDE 2008, pp. 150-159.
    • Proc. IEEE ICDE 2008 , pp. 150-159
    • Aggarwal, C.C.1    Yu, P.S.2
  • 2
    • 70350664429 scopus 로고    scopus 로고
    • Frequent pattern mining with uncertain data
    • C.C. Aggarwal et al. Frequent pattern mining with uncertain data. In Proc. KDD 2009, pp. 29-37.
    • Proc. KDD 2009 , pp. 29-37
    • Aggarwal, C.C.1
  • 3
    • 0001882616 scopus 로고    scopus 로고
    • Fast algorithms for mining association rules
    • R. Agrawal and R. Srikant. Fast algorithms for mining association rules. In Proc. VLDB 1994, pp. 487-499.
    • Proc. VLDB 1994 , pp. 487-499
    • Agrawal, R.1    Srikant, R.2
  • 4
    • 0027621699 scopus 로고    scopus 로고
    • Mining association rules between sets of items in large databases
    • R. Agrawal et al. Mining association rules between sets of items in large databases. In Proc. ACM SIGMOD 1993, pp. 207-216.
    • Proc. ACM SIGMOD 1993 , pp. 207-216
    • Agrawal, R.1
  • 5
    • 23044517681 scopus 로고    scopus 로고
    • Constraint-based rule mining in large, dense databases
    • July
    • R.J. Bayardo Jr. et al. Constraint-based rule mining in large, dense databases. In Data Mining and Knowledge Discovery, 4(2-3), July 2000, pp. 217-240.
    • (2000) Data Mining and Knowledge Discovery , vol.4 , Issue.2-3 , pp. 217-240
    • Bayardo Jr., R.J.1
  • 6
    • 70350697587 scopus 로고    scopus 로고
    • Probabilistic frequent itemset mining in uncertain databases
    • T. Bernecker et al. Probabilistic frequent itemset mining in uncertain databases. In Proc. KDD 2009, pp. 119-127.
    • Proc. KDD 2009 , pp. 119-127
    • Bernecker, T.1
  • 7
    • 0031161999 scopus 로고    scopus 로고
    • Beyond market baskets: Generalizing association rules to correlations
    • S. Brin et al. Beyond market baskets: generalizing association rules to correlations. In Proc. ACM SIGMOD 1997, pp. 265-276.
    • Proc. ACM SIGMOD 1997 , pp. 265-276
    • Brin, S.1
  • 8
    • 35248856358 scopus 로고    scopus 로고
    • Mining itemsets in the presence of missing values
    • T. Calders et al. Mining itemsets in the presence of missing values. In Proc. ACM SAC 2007, pp. 404-408.
    • Proc. ACM SAC 2007 , pp. 404-408
    • Calders, T.1
  • 9
    • 52649165058 scopus 로고    scopus 로고
    • Probabilistic verifiers: Evaluating constrained nearest-neighbor queries over uncertain data
    • R. Cheng et al. Probabilistic verifiers: evaluating constrained nearest-neighbor queries over uncertain data. In Proc. IEEE ICDE 2008, pp. 973-982.
    • Proc. IEEE ICDE 2008 , pp. 973-982
    • Cheng, R.1
  • 10
    • 38049177468 scopus 로고    scopus 로고
    • Mining frequent itemsets from uncertain data
    • C.-K. Chui et al. Mining frequent itemsets from uncertain data. In Proc. PAKDD 2007, pp. 47-58.
    • Proc. PAKDD 2007 , pp. 47-58
    • Chui, C.-K.1
  • 11
    • 26444512067 scopus 로고    scopus 로고
    • Probabilistic spatial queries on existentially uncertain data
    • X. Dai et al. Probabilistic spatial queries on existentially uncertain data. In Proc. SSTD 2005, pp. 400-417.
    • Proc. SSTD 2005 , pp. 400-417
    • Dai, X.1
  • 12
    • 33751044944 scopus 로고    scopus 로고
    • A probability analysis for candidate-based frequent itemset algorithms
    • N. Dexters et al. A probability analysis for candidate-based frequent itemset algorithms. In Proc. ACM SAC 2006, pp. 541-545.
    • Proc. ACM SAC 2006 , pp. 541-545
    • Dexters, N.1
  • 13
    • 0033892546 scopus 로고    scopus 로고
    • Efficient mining of constrained correlated sets
    • G. Grahne et al. Efficient mining of constrained correlated sets. In Proc. IEEE ICDE 2000, pp. 512-521.
    • Proc. IEEE ICDE 2000 , pp. 512-521
    • Grahne, G.1
  • 14
    • 0039253846 scopus 로고    scopus 로고
    • Mining frequent patterns without candidate generation
    • J. Han et al. Mining frequent patterns without candidate generation. In Proc. ACM SIGMOD 2000, pp. 1-12.
    • Proc. ACM SIGMOD 2000 , pp. 1-12
    • Han, J.1
  • 15
    • 35248846435 scopus 로고    scopus 로고
    • Optimizing hypergraph transversal computation with an anti-monotone constraint
    • C. Hébert et al. Optimizing hypergraph transversal computation with an anti-monotone constraint. In Proc. ACM SAC 2007, pp. 443-444.
    • Proc. ACM SAC 2007 , pp. 443-444
    • Hébert, C.1
  • 16
    • 3142594274 scopus 로고    scopus 로고
    • Efficient dynamic mining of constrained frequent sets
    • Dec.
    • L.V.S. Lakshmanan, C.K.-S. Leung, and R. Ng. Efficient dynamic mining of constrained frequent sets. ACM TODS, 28(4), Dec. 2003, pp. 337-389.
    • (2003) ACM TODS , vol.28 , Issue.4 , pp. 337-389
    • Lakshmanan, L.V.S.1    Leung, C.K.-S.2    Ng, R.3
  • 17
    • 56749181484 scopus 로고    scopus 로고
    • Frequent pattern mining for kernel trace data
    • C. LaRosa et al. Frequent pattern mining for kernel trace data. In Proc. ACM SAC 2008, pp. 880-885.
    • Proc. ACM SAC 2008 , pp. 880-885
    • Larosa, C.1
  • 18
    • 72949086846 scopus 로고    scopus 로고
    • Frequent spatio-temporal patterns in trajectory data warehouses
    • L. Leonardi et al. Frequent spatio-temporal patterns in trajectory data warehouses. In Proc. ACM SAC 2009, pp. 1433-1440.
    • Proc. ACM SAC 2009 , pp. 1433-1440
    • Leonardi, L.1
  • 19
    • 70450243146 scopus 로고    scopus 로고
    • Efficient algorithms for mining constrained frequent patterns from uncertain data
    • C.K.-S. Leung and D.A. Brajczuk. Efficient algorithms for mining constrained frequent patterns from uncertain data. In Proc. U '09, pp. 9-18.
    • Proc. U '09 , pp. 9-18
    • Leung, C.K.-S.1    Brajczuk, D.A.2
  • 20
    • 70350635438 scopus 로고    scopus 로고
    • Mining uncertain data for constrained frequent sets
    • C.K.-S. Leung and D.A. Brajczuk. Mining uncertain data for constrained frequent sets. In Proc. IDEAS 2009, pp. 109-120.
    • Proc. IDEAS 2009 , pp. 109-120
    • Leung, C.K.-S.1    Brajczuk, D.A.2
  • 21
    • 67649641426 scopus 로고    scopus 로고
    • Mining of frequent itemsets from streams of uncertain data
    • C.K.-S. Leung and B. Hao. Mining of frequent itemsets from streams of uncertain data. In Proc. IEEE ICDE 2009, pp. 1663-1670.
    • Proc. IEEE ICDE 2009 , pp. 1663-1670
    • Leung, C.K.-S.1    Hao, B.2
  • 22
    • 44649151137 scopus 로고    scopus 로고
    • A tree-based approach for frequent pattern mining from uncertain data
    • C.K.-S. Leung et al. A tree-based approach for frequent pattern mining from uncertain data. In Proc. PAKDD 2008, pp. 653-661.
    • Proc. PAKDD 2008 , pp. 653-661
    • Leung, C.K.-S.1
  • 23
    • 35248836871 scopus 로고    scopus 로고
    • Maintenance of maximal frequent itemsets in large databases
    • W. Lian et al. Maintenance of maximal frequent itemsets in large databases. In Proc. ACM SAC 2007, pp. 388-392.
    • Proc. ACM SAC 2007 , pp. 388-392
    • Lian, W.1
  • 24
    • 33751025160 scopus 로고    scopus 로고
    • Looking for monotonicity properties of a similarity constraint on sequences
    • I. Mitasiunaite and J.-F. Boulicaut. Looking for monotonicity properties of a similarity constraint on sequences. In Proc. ACM SAC 2006, pp. 546-552.
    • Proc. ACM SAC 2006 , pp. 546-552
    • Mitasiunaite, I.1    Boulicaut, J.-F.2
  • 25
    • 0032092760 scopus 로고    scopus 로고
    • Exploratory mining and pruning optimizations of constrained associations rules
    • R.T. Ng et al. Exploratory mining and pruning optimizations of constrained associations rules. In Proc. ACM SIGMOD 1998, pp. 13-24.
    • Proc. ACM SIGMOD 1998 , pp. 13-24
    • Ng, R.T.1
  • 26
    • 0035016447 scopus 로고    scopus 로고
    • Mining frequent itemsets with convertible constraints
    • J. Pei et al. Mining frequent itemsets with convertible constraints. In Proc. IEEE ICDE 2001, pp. 433-442.
    • Proc. IEEE ICDE 2001 , pp. 433-442
    • Pei, J.1
  • 27
    • 67649641455 scopus 로고    scopus 로고
    • Decision trees for uncertain data
    • S. Tsang et al. Decision trees for uncertain data. In Proc. IEEE ICDE 2009, pp. 441-444.
    • Proc. IEEE ICDE 2009 , pp. 441-444
    • Tsang, S.1
  • 28
    • 56749179979 scopus 로고    scopus 로고
    • Mining fault-tolerant frequent patterns efficiently with powerful pruning
    • J.-J. Zeng et al. Mining fault-tolerant frequent patterns efficiently with powerful pruning. In Proc. ACM SAC 2008, pp. 927-931.
    • Proc. ACM SAC 2008 , pp. 927-931
    • Zeng, J.-J.1
  • 29
    • 57149143965 scopus 로고    scopus 로고
    • Finding frequent items in probabilistic data
    • Q. Zhang et al. Finding frequent items in probabilistic data. In Proc. ACM SIGMOD 2008, pp. 819-832.
    • Proc. ACM SIGMOD 2008 , pp. 819-832
    • Zhang, Q.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.