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Volumn 180, Issue 6, 2010, Pages 873-885

An approach to discovering multi-temporal patterns and its application to financial databases

Author keywords

Association rule; Associative financial movement; Data mining; Multi temporal pattern

Indexed keywords

ASSOCIATION RULE MINING; BUSINESS INTELLIGENCE; CANDIDATE PATTERNS; CHINESE MAINLAND; DATABASE SCANS; DECISION SUPPORTS; HONG-KONG; INVESTMENT DECISIONS; KEY ISSUES; MANAGERIAL DECISION; MINING ALGORITHMS; MULTI-TEMPORAL; STOCK MARKET; TEMPORAL ASSOCIATION; TEMPORAL DATABASE;

EID: 73149104367     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2009.08.026     Document Type: Article
Times cited : (13)

References (37)
  • 4
    • 0020849266 scopus 로고
    • Maintaining knowledge about temporal intervals
    • Allen J.F. Maintaining knowledge about temporal intervals. Communications of the ACM 26 11 (1983) 832-P843
    • (1983) Communications of the ACM , vol.26 , Issue.11
    • Allen, J.F.1
  • 5
    • 38349081558 scopus 로고    scopus 로고
    • Efficient strategies for tough aggregate constraint-based sequential pattern mining
    • Chen E., Cao H., Li Q., and Qian T. Efficient strategies for tough aggregate constraint-based sequential pattern mining. Information Sciences 178 6 (2008) 1498-1518
    • (2008) Information Sciences , vol.178 , Issue.6 , pp. 1498-1518
    • Chen, E.1    Cao, H.2    Li, Q.3    Qian, T.4
  • 7
    • 33749569695 scopus 로고    scopus 로고
    • Constraint-based sequential pattern mining: the consideration of recency and compactness
    • Chen Y.-L., and Hu Y.-H. Constraint-based sequential pattern mining: the consideration of recency and compactness. Decision Support Systems 42 2 (2006) 1203-1215
    • (2006) Decision Support Systems , vol.42 , Issue.2 , pp. 1203-1215
    • Chen, Y.-L.1    Hu, Y.-H.2
  • 8
    • 33750553538 scopus 로고    scopus 로고
    • Mining temporal patterns from sequence database of interval-based events
    • FSKD
    • Y.-L. Chen, S.-Y. Wu, Mining temporal patterns from sequence database of interval-based events, in: FSKD 2006, LNAI 4223, 2006, pp. 586-595.
    • (2006) LNAI , vol.4223 , pp. 586-595
    • Chen, Y.-L.1    Wu, S.-Y.2
  • 9
    • 84947768200 scopus 로고    scopus 로고
    • Finding similar time series, in: J
    • Komorowski et al, Eds, Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery, Springer, Trondheim, Norway
    • G. Das, D. Gunopulos, H. Mannila, Finding similar time series, in: J. Komorowski et al. (Eds), Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery, LNAI 1263, Springer, Trondheim, Norway, 1997, pp. 88-100.
    • (1997) LNAI , vol.1263 , pp. 88-100
    • Das, G.1    Gunopulos, D.2    Mannila, H.3
  • 10
    • 73149116915 scopus 로고    scopus 로고
    • G. Das, K.I. Lin, H. Mannila, Rule discovery from time series, in: Proceedings of the Third International Conference on Knowledge Discovery and Data Mining, 1998, pp. 16-22.
    • G. Das, K.I. Lin, H. Mannila, Rule discovery from time series, in: Proceedings of the Third International Conference on Knowledge Discovery and Data Mining, 1998, pp. 16-22.
  • 11
    • 34248393105 scopus 로고    scopus 로고
    • First-order temporal pattern mining with regular expression constraints
    • De Amo S., and Furtado D.A. First-order temporal pattern mining with regular expression constraints. Data and Knowledge Engineering 62 3 (2007) 401-420
    • (2007) Data and Knowledge Engineering , vol.62 , Issue.3 , pp. 401-420
    • De Amo, S.1    Furtado, D.A.2
  • 13
    • 84943264048 scopus 로고    scopus 로고
    • F. Hoppner, Discovery of temporal patterns - learning rules about the qualitative behaviour of time series, in: PKDD'01, No. 2168 of LNAI, Freiburg, Germany, 2001, pp. 192-203.
    • F. Hoppner, Discovery of temporal patterns - learning rules about the qualitative behaviour of time series, in: PKDD'01, No. 2168 of LNAI, Freiburg, Germany, 2001, pp. 192-203.
  • 14
    • 34948870441 scopus 로고    scopus 로고
    • Discovery of maximum length frequent itemsets
    • Hu T., Sung S.Y., Xiong H., and Fu Q. Discovery of maximum length frequent itemsets. Information Sciences 178 1 (2008) 69-87
    • (2008) Information Sciences , vol.178 , Issue.1 , pp. 69-87
    • Hu, T.1    Sung, S.Y.2    Xiong, H.3    Fu, Q.4
  • 15
    • 0346972419 scopus 로고    scopus 로고
    • Deriving two-stage learning sequences from knowledge in fuzzy sequential pattern mining
    • Hu Y.-C., Tzeng G.-H., and Chen C.-M. Deriving two-stage learning sequences from knowledge in fuzzy sequential pattern mining. Information Sciences 159 1-2 (2004) 69-86
    • (2004) Information Sciences , vol.159 , Issue.1-2 , pp. 69-86
    • Hu, Y.-C.1    Tzeng, G.-H.2    Chen, C.-M.3
  • 16
    • 0005482588 scopus 로고    scopus 로고
    • Causality and cointegration of stock markets among the United States, Japan and South China growth triangle
    • Huang B.-N., Yang C.-W., and Hu W.-S. Causality and cointegration of stock markets among the United States, Japan and South China growth triangle. International Review of Financial Analysis 9 3 (2000) 281-297
    • (2000) International Review of Financial Analysis , vol.9 , Issue.3 , pp. 281-297
    • Huang, B.-N.1    Yang, C.-W.2    Hu, W.-S.3
  • 19
    • 34250336422 scopus 로고    scopus 로고
    • An efficient algorithm for mining frequent inter-transaction patterns
    • Lee A.J.T., and Wang C.-S. An efficient algorithm for mining frequent inter-transaction patterns. Information Sciences 177 17 (2007) 3453-3476
    • (2007) Information Sciences , vol.177 , Issue.17 , pp. 3453-3476
    • Lee, A.J.T.1    Wang, C.-S.2
  • 20
    • 64549108460 scopus 로고    scopus 로고
    • Mining frequent trajectory patterns in spatial-temporal databases
    • Lee J.T., Chen Y., and Ip W.-C. Mining frequent trajectory patterns in spatial-temporal databases. Information Sciences 179 13 (2009) 2218-2231
    • (2009) Information Sciences , vol.179 , Issue.13 , pp. 2218-2231
    • Lee, J.T.1    Chen, Y.2    Ip, W.-C.3
  • 21
    • 34250336422 scopus 로고    scopus 로고
    • An efficient algorithm for mining frequent inter-transaction patterns
    • Lee J.T., and Wang C.-S. An efficient algorithm for mining frequent inter-transaction patterns. Information Sciences 177 17 (2007) 3453-3476
    • (2007) Information Sciences , vol.177 , Issue.17 , pp. 3453-3476
    • Lee, J.T.1    Wang, C.-S.2
  • 23
    • 31944451673 scopus 로고    scopus 로고
    • Looking into the seeds of time: discovering temporal patterns in large transaction sets
    • Li Y., Zhu S., Wang X.S., and Jajoodia S. Looking into the seeds of time: discovering temporal patterns in large transaction sets. Information Sciences 176 8 (2006) 1003-1031
    • (2006) Information Sciences , vol.176 , Issue.8 , pp. 1003-1031
    • Li, Y.1    Zhu, S.2    Wang, X.S.3    Jajoodia, S.4
  • 24
    • 5144226703 scopus 로고    scopus 로고
    • Interactive sequence discovery by incremental mining
    • Lin M.-Y., and Lee S.-Y. Interactive sequence discovery by incremental mining. Information Sciences 165 3-4 (2004) 187-205
    • (2004) Information Sciences , vol.165 , Issue.3-4 , pp. 187-205
    • Lin, M.-Y.1    Lee, S.-Y.2
  • 25
    • 51349163865 scopus 로고    scopus 로고
    • Fast discovering of sequential patterns in large databases using effective time-indexing
    • Lin M.-Y., Hsueh S.-C., and Chang C.-W. Fast discovering of sequential patterns in large databases using effective time-indexing. Information Sciences 178 22 (2008) 4228-4245
    • (2008) Information Sciences , vol.178 , Issue.22 , pp. 4228-4245
    • Lin, M.-Y.1    Hsueh, S.-C.2    Chang, C.-W.3
  • 26
    • 51349163865 scopus 로고    scopus 로고
    • Fast discovery of sequential patterns in large databases using effective time-indexing
    • Lin M.-Y., Hsueh S.-C., and Chang C.-W. Fast discovery of sequential patterns in large databases using effective time-indexing. Information Sciences 178 22 (2008) 4228-4245
    • (2008) Information Sciences , vol.178 , Issue.22 , pp. 4228-4245
    • Lin, M.-Y.1    Hsueh, S.-C.2    Chang, C.-W.3
  • 28
    • 0034410336 scopus 로고    scopus 로고
    • Red chips or H-shares: which China-backed securities process information the fastest
    • Poon W.P.H., and Fund H.-G. Red chips or H-shares: which China-backed securities process information the fastest. Journal of Multinational Financial Management 10 (2000) 315-343
    • (2000) Journal of Multinational Financial Management , vol.10 , pp. 315-343
    • Poon, W.P.H.1    Fund, H.-G.2
  • 29
    • 22844456088 scopus 로고    scopus 로고
    • C.P. Rainsford, J.F. Roddic, Adding temporal semantics to association rules, in: Proceedings of the Third European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD '99, Prague, Czech Republic. September 15-18, 1999, pp. 504-509.
    • C.P. Rainsford, J.F. Roddic, Adding temporal semantics to association rules, in: Proceedings of the Third European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD '99, Prague, Czech Republic. September 15-18, 1999, pp. 504-509.
  • 30
    • 0001141091 scopus 로고    scopus 로고
    • The effect of market segmentation on stock prices: the China syndrome
    • Sun Q., and Tong W.H.S. The effect of market segmentation on stock prices: the China syndrome. Journal of Banking and Finance 24 (2000) 1875-1902
    • (2000) Journal of Banking and Finance , vol.24 , pp. 1875-1902
    • Sun, Q.1    Tong, W.H.S.2
  • 31
    • 62249183038 scopus 로고    scopus 로고
    • FIUT: a new method for mining frequent itemsets
    • Tsay T.-J., Hsu T.-J., and Yu J.-R. FIUT: a new method for mining frequent itemsets. Information Sciences 179 11 (2009) 1724-1737
    • (2009) Information Sciences , vol.179 , Issue.11 , pp. 1724-1737
    • Tsay, T.-J.1    Hsu, T.-J.2    Yu, J.-R.3
  • 32
    • 34250202878 scopus 로고    scopus 로고
    • ARMADA - an algorithm for discovering richer relative temporal association rules from interval-based data
    • Winarko E., and Roddick J.F. ARMADA - an algorithm for discovering richer relative temporal association rules from interval-based data. Data and Knowledge Engineering 63 1 (2007) 76-90
    • (2007) Data and Knowledge Engineering , vol.63 , Issue.1 , pp. 76-90
    • Winarko, E.1    Roddick, J.F.2
  • 33
    • 73149085381 scopus 로고    scopus 로고
    • Wind Financial Databases, Shanghai Wind Information Co., Ltd., http://www.wind.com.cn/.
    • Wind Financial Databases, Shanghai Wind Information Co., Ltd., http://www.wind.com.cn/.
  • 35
    • 73149102165 scopus 로고    scopus 로고
    • Mining delayed association rules based on temporal data
    • (in Chinese)
    • Yu W., and Chen G. Mining delayed association rules based on temporal data. Computer Application and Research 12 (2002) 19-22 (in Chinese)
    • (2002) Computer Application and Research , vol.12 , pp. 19-22
    • Yu, W.1    Chen, G.2
  • 36
    • 0034826102 scopus 로고    scopus 로고
    • SPADE: an efficient algorithm for mining frequent sequences
    • Zaki M.J. SPADE: an efficient algorithm for mining frequent sequences. Machine Learning 42 1/2 (2000) 31-60
    • (2000) Machine Learning , vol.42 , Issue.1-2 , pp. 31-60
    • Zaki, M.J.1
  • 37
    • 36148947566 scopus 로고    scopus 로고
    • Discovering during-temporal patterns (DTPs) in large temporal databases
    • Zhang L., Chen G., Brijs T., and Zhang X. Discovering during-temporal patterns (DTPs) in large temporal databases. Expert Systems with Applications 34 2 (2008) 1178-1189
    • (2008) Expert Systems with Applications , vol.34 , Issue.2 , pp. 1178-1189
    • Zhang, L.1    Chen, G.2    Brijs, T.3    Zhang, X.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.