下边深陷
发表于 2025-3-25 07:20:28
Lee Giles,Marc Smith,Haizheng Zhangup-to-date results.fast-track conference proceedings.state-of-the-art report
小步舞
发表于 2025-3-25 10:52:16
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SEVER
发表于 2025-3-25 11:45:26
0302-9743 ns the p- ceedings for the Second International Workshop on Social Network Analysis (SNAKDD 2008). The annual workshop co-locates with the ACM SIGKDD - ternational Conference on Knowledge Discovery and Data Mining (KDD). The second SNAKDD workshop was held with KDD 2008 and received more than 32 sub
MUTE
发表于 2025-3-25 19:15:29
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抱狗不敢前
发表于 2025-3-25 23:31:30
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陶器
发表于 2025-3-26 01:26:48
Mika Kuuskankare,Mikael Laursonre accurate) compared to using more traditional features such as descriptive node attributes and structural features. The experiments also show that a combination of all three types of attributes results in the best precision-recall trade-off.
Psa617
发表于 2025-3-26 04:19:43
https://doi.org/10.1007/978-3-540-85035-91) SGE does not exhibit a resolution limit on sparse graphs in which other approaches do, and that (2) modularity and the compression-based algorithms, including SGE, behave similarly on graphs not subject to the resolution limit.
In-Situ
发表于 2025-3-26 10:45:13
Community Detection Using a Measure of Global Influence,ere nodes have more influence over each other than over nodes outside the community. We evaluate our approach on several networks and show that it often outperforms the edge-based modularity algorithm.
自制
发表于 2025-3-26 13:03:14
Using Friendship Ties and Family Circles for Link Prediction,re accurate) compared to using more traditional features such as descriptive node attributes and structural features. The experiments also show that a combination of all three types of attributes results in the best precision-recall trade-off.
malapropism
发表于 2025-3-26 17:48:56
Information Theoretic Criteria for Community Detection,1) SGE does not exhibit a resolution limit on sparse graphs in which other approaches do, and that (2) modularity and the compression-based algorithms, including SGE, behave similarly on graphs not subject to the resolution limit.