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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On Burst Detection and Prediction in Retweeting Sequence978-0-230-35425-8

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Resampling-Based Gap Analysis for Detecting Nodes with High Centrality on Large Social Network978-1-137-38812-4

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Lecture Notes in Computer Scienced participants, and we prove that BARGS can acquire the solution with a guaranteed performance bound. The proposed algorithm was implemented in Facebook, and experimental results demonstrate that social groups generated by the proposed algorithm significantly outperform the baseline solutions.

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APEX

legacy

Lecture Notes in Computer Scienceedict bursts using classifiers based on the extracted features. Our empirical study of the Sina Weibo data shows the feasibility of burst prediction using appropriately extracted features and classic classifiers.

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Teena Steger,Klaus Drechsler,Stefan Wesargersational platform – as opposed to other users who primarily discuss topical contents. The implication of these findings is that within a single online social network, activities of users may have very different semantics; thus, tasks like community detection and recommendation may not be accomplis

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