Probabilistic Event Pattern Discovery

Detecting occurrences of complex events in an event stream requires designing queries that describe real-world situations. However, specifying complex event patterns is a challenging task that requires domain and system specific knowledge. Novel approaches are required that automatically identify patterns of potential interest in a heavy flow of events.

[1]  Roque Marín,et al.  ClaSP: An Efficient Algorithm for Mining Frequent Closed Sequences , 2013, PAKDD.

[2]  Philip S. Yu,et al.  Mining Frequent Patterns in Data Streams at Multiple Time Granularities , 2002 .

[3]  Ling Chen,et al.  Mining frequent items in data stream using time fading model , 2014, Inf. Sci..

[4]  Mohammed J. Zaki,et al.  SPADE: An Efficient Algorithm for Mining Frequent Sequences , 2004, Machine Learning.

[5]  Bart Goethals,et al.  Survey on Frequent Pattern Mining , 2003 .

[6]  Ramakrishnan Srikant,et al.  Mining sequential patterns , 1995, Proceedings of the Eleventh International Conference on Data Engineering.

[7]  Hongjun Lu,et al.  False Positive or False Negative: Mining Frequent Itemsets from High Speed Transactional Data Streams , 2004, VLDB.

[8]  Xifeng Yan,et al.  CloSpan: Mining Closed Sequential Patterns in Large Datasets , 2003, SDM.

[9]  Qiming Chen,et al.  PrefixSpan,: mining sequential patterns efficiently by prefix-projected pattern growth , 2001, Proceedings 17th International Conference on Data Engineering.

[10]  Philip S. Yu,et al.  Moment: maintaining closed frequent itemsets over a stream sliding window , 2004, Fourth IEEE International Conference on Data Mining (ICDM'04).

[11]  Rajeev Motwani,et al.  Approximate Frequency Counts over Data Streams , 2012, VLDB.

[12]  Giordano Tamburrelli,et al.  Learning from the past: automated rule generation for complex event processing , 2014, DEBS '14.

[13]  Won Suk Lee,et al.  Finding recent frequent itemsets adaptively over online data streams , 2003, KDD '03.

[14]  Sharma Chakravarthy,et al.  Composite Events for Active Databases: Semantics, Contexts and Detection , 1994, VLDB.