Discovery of Periodic Patterns in Sequence Data: A Variance-Based Approach

Published Online:https://doi.org/10.1287/ijoc.1110.0457

References

  • Adomavicius G., Sankaranarayanan R., Sen S., Tuzhilin A. Incorporating contextual information in recommender systems using a multidimensional approach. ACM Trans. Inform. Systems (2005) 23(1):103–145CrossrefGoogle Scholar
  • Aggarwal R. C., Aggarwal C. C., Parsad V. V. V. Depth first generation of long patterns. Internat. Conf. Knowledge Discovery Data Mining (2000) (ACM, New York) 108–118CrossrefGoogle Scholar
  • Agrawal R., Srikant R. Fast algorithms for mining association rules. Proc. 20th VLDB Conf. (1994) Santiago, Chile(Morgan Kaufmann, San Francisco) 487–499Google Scholar
  • Bayardo R. J., Tiwary A., Franklin M. Efficiently mining long patterns from databases. Porc. 1998 ACM SIGMOD Intertant. Conf. Management Data (1998) (ACM, New York) 85–93CrossrefGoogle Scholar
  • Han J., Dong G., Yin Y. Efficient mining partial periodic patterns in time series database. Proc. Internat. Conf. Data Engrg. (1999) (IEEE Computer Society, Washington, DC) 106–115Google Scholar
  • Han J., Gong W., Yin Y. Mining segment-wise periodic patterns in time-related databases. Proc. KDD 1998 (1998) (American Association for Artificial Intelligence, Menlo Park, CA) 214–218Google Scholar
  • Han J., Jian P., Yin Y., Mao R. Mining frequent patterns without candidate generation: A frequent-pattern tree approach. Data Mining Knowledge Discovery (2004) 8(1):53–87CrossrefGoogle Scholar
  • Ma S., Hellerstein J. Mining partially periodic event patterns with unknown periods. Proc. Internat. Conf. Data Engrg. (2001) (IEEE Computer Society, Washington, DC) 205–214Google Scholar
  • Mannila H., Toivonen H., Verkamo A. Discovery of frequent episodes in event sequences. Data Mining Knowledge Discovery (1997) 1(3):259–289CrossrefGoogle Scholar
  • Ross S. M.Introduction to Probability and Statistics for Engineers and Scientists (1987) (John Wiley & Sons, New York) Google Scholar
  • Wise L. Moving towards a proactive approach to BI. (2009) . Dashboard Insight (May 13), 2009, http://www.dash-board-insight.com/articles/new-concepts-in-business-intelligence/moving-towards-a-proactive-approach-to-bi.aspxGoogle Scholar
  • Yang J., Wang W., Yu P. Mining asynchronous periodic patterns in time series data. IEEE Trans. Knowledge Data Engrg. (2003) 15(3):613–628CrossrefGoogle Scholar
  • Yang J., Wang W., Yu P. Mining surprising periodic patterns. Data Mining Knowledge Discovery (2004) 9(2):189–216CrossrefGoogle Scholar
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