Titlebook: Data Mining for Social Network Data; Nasrullah Memon,Jennifer Jie Xu,Hsinchun Chen Book 2010 Springer Science+Business Media, LLC 2010 Map

craving

https://doi.org/10.1007/978-981-10-5269-9orks. Discovering communities from such bipartite networks is important for finding similar items and for understanding overall network structures. In order to evaluate the quality of divisions of normal (unipartite) networks, Newman’s modularity is widely used. Recently, modularities for bipartite

知識分子

織物

Visual-Acuity

廚師

Data Mining for Social Network Data978-1-4419-6287-4Series ISSN 1934-3221 Series E-ISSN 1934-3213

言外之意

Soil Environment in Sago Palm Forestry. A discrete dynamic model is constructed to investigate the evolution of the network. Our analysis offers direct confirmation for the existence of preferential attachment in the air transportation network. We conclude that both an aging effect and preferential attachment are the two mechanisms driving the network evolution.

Harpoon

極微小

1934-3221 dents in sociology, computer science and statistics.The reseDriven by counter-terrorism efforts, marketing analysis and an explosion in online social networking in recent years, data mining has moved to the forefront of information science. This proposed Special Issue on Data Mining for Social Netwo

Volatile-Oils

molest

Christliche Sagen (Exempel und Legenden), been accompanied by the increasing popularity of social networking sites such as FaceBook and MySpace. As a result, research on ., or simply ., has attracted much attention from both academics and practitioners.