Sciweavers

Share
ICDM
2007
IEEE

Finding Cohesive Clusters for Analyzing Knowledge Communities

12 years 1 months ago
Finding Cohesive Clusters for Analyzing Knowledge Communities
Documents and authors can be clustered into “knowledge communities” based on the overlap in the papers they cite. We introduce a new clustering algorithm, Streemer, which finds cohesive foreground clusters embedded in a diffuse background, and use it to identify knowledge communities as foreground clusters of papers which share common citations. To analyze the evolution of these communities over time, we build predictive models with features based on the citation structure, the vocabulary of the papers, and the affiliations and prestige of the authors. Findings include that scientific knowledge communities tend to grow more rapidly if their publications build on diverse information and if they use a narrow vocabulary.
Vasileios Kandylas, S. Phineas Upham, Lyle H. Unga
Added 03 Jun 2010
Updated 03 Jun 2010
Type Conference
Year 2007
Where ICDM
Authors Vasileios Kandylas, S. Phineas Upham, Lyle H. Ungar
Comments (0)
books