An Efficient Heuristic Search for Real-Time Frequent Pattern Mining

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An Efficient Heuristic Search for Real-Time Frequent Pattern Mining
Real-time frequent pattern mining for business intelligence systems are currently in the focal area of research. In a number of areas of doing business, especially in the arena of supply chain management systems, real-time frequent pattern mining is in need. The need is being felt more due to the possibility of real-time knowledge discovery along with the gradual acceptance of technologies like RFID and grid computing and the huge amount of possibilities they promise for real-time decision making like supplychain optimization. In this paper, we describe a domain-independent heuristic, h1-max and a heuristic search algorithm, BDFS(b)-h1-max for real-time frequent pattern mining, even using limited computer memory. Empirical evaluations show that the techniques being presented can make a fair estimation of the set of the probable frequent patterns and completes the search much faster than the existing algorithms.
Rajanish Dass, Ambuj Mahanti
Added 11 Jun 2010
Updated 11 Jun 2010
Type Conference
Year 2006
Authors Rajanish Dass, Ambuj Mahanti
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