Titlebook: Advances in Social Network Mining and Analysis; Second International Lee Giles,Marc Smith,Haizheng Zhang Conference proceedings 2010 The Ed

下邊深陷

Lee Giles,Marc Smith,Haizheng Zhangup-to-date results.fast-track conference proceedings.state-of-the-art report

小步舞

SEVER

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

抱狗不敢前

陶器

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

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

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

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

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.