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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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Examination of the Cervical Spine, and have excellent overall performance. The vertical representation allows generating patterns and calculating their supports without performing costly database scans. However, a crucial performance bottleneck of vertical algorithms is that they use a generate-candidate-and-test approach that can g
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W. Poewe,F. Gerstenbrand,G. Ransmayret so that the number of final influenced nodes can be maximized. In this paper, we propose three strategies to solve this problem. First, Billboard strategy chooses the most influential nodes as the seeds. Second, Handbill strategy chooses the most cost-effective nodes as the seeds. Finally, Combin
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Franz Gerstenbrand,Werner Poewe,Gerald Sternvolving social network data. We propose an algorithm, Persistent Community Detection (PCD), to identify those communities that exhibit persistent behavior over time, for usage in such settings. Our motivation is to distinguish between steady-state network activity, and impermanent behavior such as c
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W. Poewe,F. Gerstenbrand,G. Ransmayrdata, predicting a user’s next check-in place is of much interest recently. There is, however, little study on the limit of predictability of this task and its correlation with users’ demographics. These studies can give deeper insight to the prediction task and bring valuable insights to the design
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,The “Facial Points of Interest”,ch members may have certain attitude, positive or negative, toward each other, and so the network consists of a mixture of both positive and negative relationships. Our goal is to predict the sign of a given relationship based on the evidences provided in the current snapshot of the network. More pr
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