Web Access Pattern Mining – A Survey

Rajimol, Achuthan Nair; Raju, G.

doi:10.1007/978-3-642-27872-3_4

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Serial Frequent Sequence Mining1

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2014

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“…The algorithm uses a Web access pattern tree (WAP-tree) as a compressed representation of the sequence database and a conditional search tree-projection mechanism for growing sequence patterns. Rajimol and Raju [46] surveyed several WAP-tree based extensions which improve the data structure and projection mechanism of WAP-miner.…”

Section: Serial Frequent Sequence Miningmentioning

confidence: 99%

Big Data Frequent Pattern Mining

Anastasiu

Iverson

Smith

et al. 2014

Frequent Pattern Mining

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Frequent pattern mining is an essential data mining task, with a goal of discovering knowledge in the form of repeated patterns. Many efficient pattern mining algorithms have been discovered in the last two decades, yet most do not scale to the type of data we are presented with today, the so-called "Big Data". Scalable parallel algorithms hold the key to solving the problem in this context. In this chapter, we review recent advances in parallel frequent pattern mining, analyzing them through the Big Data lens. We identify three areas as challenges to designing parallel frequent pattern mining algorithms: memory scalability, work partitioning, and load balancing. With these challenges as a frame of reference, we extract and describe key algorithmic design patterns from the wealth of research conducted in this domain.

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Section: Serial Frequent Sequence Miningmentioning

confidence: 99%