Titlebook: Advances in Knowledge Discovery and Data Mining; 19th Pacific-Asia Co Tru Cao,Ee-Peng Lim,Hiroshi Motoda Conference proceedings 2015 Spring

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Osteoarticular and Soft-Tissue Tuberculosis,neither of these two algorithms needs to perform singular value decomposition (SVD) on label matrix which is used in previously mentioned approaches. Experiments are performed on several real world multi-label data sets with the number of labels ranging from hundreds to thousands, and it is shown th

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Jianhui Chen,Hui Qian,Xiaoliang Gongns. In this paper, we consider the scenarios of organizing in person friend-making social activities via online social networks (OSNs) and formulate a new research problem, namely, Hop-bounded Maximum Group Friending (HMGF), by modeling both existing friendships and the likelihood of new friend maki

tympanometry

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https://doi.org/10.1007/978-3-031-45249-9impressions on this social network. Therefore link prediction for new users is significant. However, due to the lack of sufficient active data of new users in the new social network (target network), link prediction often encounters the cold start problem. In this paper, we attempt to solve the user

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Lecture Notes in Computer Science same interest join it as well. Nevertheless, even with the interest and social tightness information available in online social networks, nowadays many social group activities still need to be coordinated manually. In this paper, therefore, we first formulate a new problem, named Participant Select

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https://doi.org/10.1007/978-3-642-38079-2n information piece in a social network can be affected by different factors. Previously, many diffusion models are proposed to consider one or several fixed factors. The factors affecting the adoption decision of a node are different from one to another and may not be seen before. For a different s

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