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Titlebook: Algorithms and Models for the Web-Graph; 7th International Wo Ravi Kumar,Dandapani Sivakumar Conference proceedings 2010 The Editor(s) (if

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41#
發(fā)表于 2025-3-28 18:11:44 | 只看該作者
42#
發(fā)表于 2025-3-28 20:00:09 | 只看該作者
Game-Theoretic Models of Information Overload in Social Networks, that capture rate competition between celebrities producing updates in such networks where users non-strategically choose a subset of celebrities to follow based on the utility derived from high quality updates as well as disutility derived from having to wade through too many updates. Our two vari
43#
發(fā)表于 2025-3-28 23:00:25 | 只看該作者
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發(fā)表于 2025-3-29 07:06:49 | 只看該作者
Die Verwendung des Schwefelkohlenstoffs,e integer .. The improved PageRank algorithm is crucial for computing a quantitative ranking of edges in a given graph. We will use the edge ranking to examine two interrelated problems – graph sparsification and graph partitioning. We can combine the graph sparsification and the partitioning algori
45#
發(fā)表于 2025-3-29 10:53:24 | 只看該作者
46#
發(fā)表于 2025-3-29 14:01:27 | 只看該作者
https://doi.org/10.1007/978-3-642-46987-9ts can be defined by many different metrics and aggregation of these metrics into a single one poses several important challenges, such as recovering this aggregation function from ground-truth, investigating the space of different clusterings, etc. In this paper, we address how to find an aggregati
47#
發(fā)表于 2025-3-29 15:42:27 | 只看該作者
Wirtschaftswissenschaftliche Beitr?geip, and wireless sensor networks. RIGs can be interpreted as a model for large randomly formed non-metric data sets. We analyze the component evolution in general RIGs, giving conditions on the existence and uniqueness of the giant component. Our techniques generalize existing methods for analysis o
48#
發(fā)表于 2025-3-29 22:11:07 | 只看該作者
49#
發(fā)表于 2025-3-30 01:04:24 | 只看該作者
Die Gravitation am Rande der Metagalaxis,ain their emergence through tractable models. In most networks, and especially in social networks, nodes have a rich set of attributes associated with them. We present the Multiplicative Attribute Graphs (MAG) model, which naturally captures the interactions between the network structure and the nod
50#
發(fā)表于 2025-3-30 06:29:01 | 只看該作者
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