Pi-CEP: Predictive Complex Event Processing using Range Queries over Historical Pattern Space - Archive ouverte HAL
Communication Dans Un Congrès Année : 2017

Pi-CEP: Predictive Complex Event Processing using Range Queries over Historical Pattern Space

Kamal Deep Singh
Julien Subercaze
Christophe Gravier
Jacques Fayolle
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Frederique Laforest

Résumé

—Predictive Complex Event Processing (CEP) constitutes the next phase of CEP evolution and provides future pre-dictive states of the partially matched complex sequences. In this paper, we demonstrate our novel predictive CEP system and show that this problem can be solved while leveraging existing data modelling, query execution and optimisation frameworks. We model the predictive detection of events over an N-dimensional historical matched sequence space. Hence, a predictive set of events can be determined by answering the range queries over the historical sequence space. In order to take advantage of range search over 1-dimensional data structures, we transform the N-dimensional space into 1-dimension using space filling z-order curve. We propose a compressed index structure to store 1-dimensional data and execute customised range query techniques. Furthermore, we propose an approximate summarisation technique , over the historical space of top-k most infrequent range queries, to cater catastrophic forgetting of older matches. Two real-world datasets are used to demonstrate the feasibility of our proposed techniques. We demonstrate that our system can efficiently predict complex events and it equips a user-friendly interface to fulfil the requirements of user-computer interaction in a real-time.
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Dates et versions

hal-01613798 , version 1 (25-10-2017)

Identifiants

  • HAL Id : hal-01613798 , version 1

Citer

Syed Gillani, Abderrahmen Kammoun, Kamal Deep Singh, Julien Subercaze, Christophe Gravier, et al.. Pi-CEP: Predictive Complex Event Processing using Range Queries over Historical Pattern Space. International Conference on Data Mining (ICDM) , Nov 2017, NEw Orleans, United States. ⟨hal-01613798⟩
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