Titlebook: Advances in Knowledge Discovery and Data Mining; 17th Pacific-Asia Co Jian Pei,Vincent S. Tseng,Guandong Xu Conference proceedings 2013 Spr

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/148609.jpg

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https://doi.org/10.1007/978-3-642-37453-1big data; recommender systems; social media mining; text classification; transfer learning

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Advances in Knowledge Discovery and Data Mining978-3-642-37453-1Series ISSN 0302-9743 Series E-ISSN 1611-3349

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General Concepts in Cancer Managementses, such an approach works well because the general population is rather homogeneous, and the subgroup encompasses clear outliers. In more complex situations however, the investigated population is a mixture of various subpopulations, and reporting all of these as interesting subgroups is undesirab

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Cardiac Complications of Malignancyrs, researchers have paid attention to frequent pattern mining from uncertain data. When handling uncertain data, UF-growth and UFP-growth are examples of well-known mining algorithms, which use the UF-tree and the UFP-tree respectively. However, these trees can be large, and thus degrade the mining

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Consequence

Cutaneous Complications of Malignancyaled by discovering interaction patterns from these meetings. An existing method mines interaction patterns from meetings using tree structures. However, such a tree-based method may not capture all kinds of triggering relations between interactions, and it may not distinguish a participant of a cer

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