Titlebook: Advances in Knowledge Discovery and Data Mining; 21st Pacific-Asia Co Jinho Kim,Kyuseok Shim,Yang-Sae Moon Conference proceedings 2017 Spri

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Jinho Kim,Kyuseok Shim,Yang-Sae MoonIncludes supplementary material: .Includes supplementary material:

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Conference proceedings 2017ext and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms; behavioral data mining; graph clustering and community detection; dimensionality reduction..

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Shannon C. Trotter,Suchita Sampath be used to explain and distinguish the groups of population. The ranking method is illustrated with an open data and then, applied to advance the educational knowledge discovery from large-scale international student assessment data, whose robust clustering into disjoint groups on three different levels of abstraction was performed in [.].

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0302-9743 ereed proceedings of the 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017. .The 129 full papers were carefully reviewed and selected from 458 submissions. They are organized in topical sections named: classification a

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Behavioral Treatment of Alcoholismbe perfectly accurate. This paper derives an optimization framework to solve this task through estimating the expertise of each annotator and the labeling difficulty for each instance. In addition, we introduce similarity metric to enable the propagation of annotations between instances.

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Shannon C. Trotter,Suchita Sampathtime periods give new insights on the customer behavior. Our approach is inspired by methods from the domain of sequence segmentation, thus benefiting from efficient exact and approximate algorithms. Experiments on a real massive retail dataset show the interest of the signatures for understanding individual customers.

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Conference proceedings 2017e Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017. .The 129 full papers were carefully reviewed and selected from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy-preserving mining