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E-Cube: multi-dimensional event sequence analysis using hierarchical pattern query sharing by Mo Liu; Elke Rundensteiner; Kara Greenfield; Chetan Gupta; Song Wang; Ismail Ari; Abhay Mehta is a scholarly article available to read on EtoBox.

What is E-Cube: multi-dimensional event sequence analysis using hierarchical pattern query sharing about?

Many modern applications, including online financial feeds, tagbased mass transit systems and RFID-based supply chain management systems transmit real-time data streams. There is a need for event stream processing technology to analyze this vast amount of sequential data to enable online operational decision making. Existing techniques such as traditional online analytical processing (OLAP) systems are not designed for real-time pattern-based operations, while state-of-the-art Complex Event Processing (CEP) systems designed for sequence detection do not support OLAP operations. We propose a novel E-Cube model which combines CEP and OLAP techniques for efficient multi-dimensional event pattern analysis at different abstraction levels. Our analysis of the interrelationships in both concept abstraction and pattern refinement among queries facilitates the composition of these queries into an integrated E-Cube hierarchy. Based on this E-Cube hierarchy, strategies of drill-down (refinement from abstract to more specific patterns) and of roll-up (generalization from specific to more abstract patterns) are developed for the efficient workload evaluation. Our proposed execution strategies r

Author

Mo Liu; Elke Rundensteiner; Kara Greenfield; Chetan Gupta; Song Wang; Ismail Ari; Abhay Mehta

Publisher

ACM

Published

2011

Language

EN