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An approach for iterative event pattern recommendation

Published: 12 July 2010 Publication History

Abstract

The need for systems that act on events is growing. Such systems require an infrastructure for detecting patterns over incoming events and tools for helping domain experts by creating or changing them. The main goal of Complex Event Processing is detecting patterns of events in near real-time in order to indicate a situation of interest. Nowadays most current Complex Event Processing systems are focused rather on run-time than on design time issues. They pay little attention to the efficient pattern generation. Moreover, in many Complex Event Processing systems, complex event patterns may change over time due to the dynamic nature of the domain. Such changes may complicate even further the specification task as the domain expert must update the patterns constantly. Therefore the experts seek for additional support for the definition of required patterns beyond expert opinion.
In this paper we present an approach and its implementation that has been designed for a recommendation based pattern generation. We believe that a recommendation based pattern generation could increase the relevance and efficiency of newly generated patterns for the problem at hand by reusing knowledge coded in existing complex event patterns.

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cover image ACM Conferences
DEBS '10: Proceedings of the Fourth ACM International Conference on Distributed Event-Based Systems
July 2010
303 pages
ISBN:9781605589275
DOI:10.1145/1827418
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 12 July 2010

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Author Tags

  1. complex event pattern generation
  2. complex event pattern reuse
  3. complex event processing
  4. pattern identification
  5. pattern recommendation

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  • (2022)Learning of complex event processing rules with genetic programmingExpert Systems with Applications: An International Journal10.1016/j.eswa.2019.04.007129:C(186-199)Online publication date: 20-Apr-2022
  • (2022)Bat4CEP: a bat algorithm for mining of complex event processing rulesApplied Intelligence10.1007/s10489-022-03256-252:13(15143-15163)Online publication date: 11-Mar-2022
  • (2018)An Unsupervised Rule Generation Approach for Online Complex Event Processing2018 IEEE 17th International Symposium on Network Computing and Applications (NCA)10.1109/NCA.2018.8548210(1-8)Online publication date: Nov-2018
  • (2017)Automatic Learning of Predictive CEP RulesProceedings of the 11th ACM International Conference on Distributed and Event-based Systems10.1145/3093742.3093917(158-169)Online publication date: 8-Jun-2017
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  • (2016)Partial pattern fulfillment and its application in event processingProceedings of the 10th ACM International Conference on Distributed and Event-based Systems10.1145/2933267.2933537(358-361)Online publication date: 13-Jun-2016
  • (2016)Automatic learning of predictive rules for complex event processingProceedings of the 10th ACM International Conference on Distributed and Event-based Systems10.1145/2933267.2933430(414-417)Online publication date: 13-Jun-2016
  • (2016)Complex event processing for the non-expert with autoCEPProceedings of the 10th ACM International Conference on Distributed and Event-based Systems10.1145/2933267.2933296(340-343)Online publication date: 13-Jun-2016
  • (2016)PACT-ART: Enrichment, Data Mining, and Complex Event Processing in the Internet of Cultural Things2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)10.1109/SITIS.2016.80(476-483)Online publication date: 2016
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