EVENTSUMMARIZER: A tool for summarizing large event sequences: [Demp Paper]

Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, EDBT'09

Volumn , Issue , 2009, Pages 1136-1139

  Kiernan, Jerry ^a   Terzi, Evimaria ^a  

^a IBM ALMADEN RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EVENT SEQUENCE; GLOBAL VIEW; INPUT SEQUENCE; OBSERVATION PERIOD; RELATIONAL DATABASE MANAGEMENT SYSTEMS; SIMPLE MODEL; TIME PERIODS; TIME-STAMP; VISUAL INTERFACE;

MANAGEMENT INFORMATION SYSTEMS;

DATABASE SYSTEMS;

EID: 70349091743     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1516360.1516497     Document Type: Conference Paper

References (7)

1. R. Agrawal and R. Srikant. Mining Sequential Patterns. In Proc. of the 11th Int'l Conference on Data Engineering, Taipei, Taiwan, March 1995.
2. D. Chudova and P. Smyth. Pattern discovery in sequences under a markov assumption. In KDD, pages 153-162, 2002.
3. J. Kiernan and E. Terzi. Constructing comprehensive summaries of large event sequences. In KDD, pages 417-425, 2008.
4. H. Mannila and H. Toivonen. Discovering generalized episodes using minimal occurrences. In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 146-151, 1996.
5. J. Pei, J. Han, and W. Wang. Constraint-based sequential pattern mining: the pattern-growth methods. J. Intell. Inf. Syst., 28(2): 133-160, 2007.
6. J. Rissanen. Modeling by shortest data description. Automatica, 14:465-471, 1978.
7. J. Yang, W. Wang, P. S. Yu, and J. Han. Mining long sequential patterns in a noisy environment. In ACM SIGMOD International Conference on Management of Data, pages 406-417, 2002.