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Titlebook: Advances in Knowledge Discovery and Data Mining; 18th Pacific-Asia Co Vincent S. Tseng,Tu Bao Ho,Hung-Yu Kao Conference proceedings 2014 Sp

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Franz Gerstenbrand,Werner Poewe,Gerald Sternining those techniques, we can improve the precision and recall by at least ten percent. Finally, we analyze the spatial and temporal patterns for positive influenza posts and tell when and where influenza epidemic is more likely to occur.
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,The “Facial Points of Interest”, datasets such as Epinions, Slashdot, and Wikipedia. In many cases it shows almost perfect prediction accuracy. Moreover, our model can also be efficiently updated as the underlying social network evolves.
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Views of Clinical Facial Photography,tems can indicate new users’ tastes according to their responses to the interview questions. In our experiments, we evaluate our methods using a public dataset for recommendations. The results show that our method leads to better performance than other baselines.
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https://doi.org/10.1007/978-2-8178-0411-8 of . is employed to extract the frequent patterns. Normally, in a given domain, a set of items can be grouped into a category and a pattern may contain the items which belong to multiple categories. In several applications, it may be useful to distinguish between the pattern having items belonging
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Clinical Examination in Orthopedicsh attention with very general proposals. In contrast, the minimal patterns remained in the shadows in particular because of their difficult extraction. In this paper, we present a generic framework for minimal patterns mining by introducing the concept of minimizable set system. This framework addre
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