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Titlebook: Machine Learning Techniques for Online Social Networks; Tansel ?zyer,Reda Alhajj Book 2018 Springer International Publishing AG, part of S

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樓主: 不幸的你
41#
發(fā)表于 2025-3-28 17:24:33 | 只看該作者
42#
發(fā)表于 2025-3-28 22:12:39 | 只看該作者
,-Hyperbolicity and the Core-Periphery Structure in Graphs,the graph to only a subset that is responsible for maximizing its .-hyperbolicity using the local dominance relationship between vertices. Furthermore, we empirically show that the hyperbolicity of a graph can be found in a set of vertices that are in close proximity and that concentrate in the core
43#
發(fā)表于 2025-3-29 00:27:57 | 只看該作者
A Framework for OSN Performance Evaluation Studies,new market opportunities like Online Social Networks (OSN). These online applications suppose a series of noticeable challenges both for researchers and developers. The applications and support systems have to deal with a high number of interactive users simultaneously connected; huge amounts of int
44#
發(fā)表于 2025-3-29 04:13:50 | 只看該作者
On the Problem of Multi-Staged Impression Allocation in Online Social Networks,lives. These OSNs contain valuable data that can be used by advertisers to better position, market and inform users of their products. In particular, friendship relationships between users in OSNs are particularly valuable—since users are likely to exert influence on their friends, algorithms can be
45#
發(fā)表于 2025-3-29 10:42:09 | 只看該作者
46#
發(fā)表于 2025-3-29 13:29:49 | 只看該作者
47#
發(fā)表于 2025-3-29 19:28:32 | 只看該作者
Centrality and Community Scoring Functions in Incomplete Networks: Their Sensitivity, Robustness, a networks are incomplete because certain edges might be missing in the construction owing to limitations in data acquisition technologies. This is an ubiquitous problem for all application areas that use network analysis ranging from social networks to hyper-linked web networks to biological network
48#
發(fā)表于 2025-3-29 21:05:28 | 只看該作者
Ameliorating Search Results Recommendation System Based on ,-Means Clustering Algorithm and Distance an issue since it makes the data big and its mining difficult. Therefore, the focus of this work is the extraction of useful data in terms of quality and time by ameliorating search results. In this paper, we propose a framework that eliminates the duplications in the first place, then making use
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