Title :
Capturing Social Data Evolution Using Graph Clustering
Author :
Giatsoglou, Maria ; Vakali, Athena
Author_Institution :
Aristotle Univ., Thessaloniki, Greece
Abstract :
The fast and unpredictable evolution of social data poses challenges for capturing user activities and complex associations. Evolving social graph clustering promises to uncover the dynamics of latent user and content patterns. This Web extra overviews evolving data clustering approaches.
Keywords :
data handling; graph theory; pattern clustering; social networking (online); capturing social data evolution; complex associations; data clustering; social graph clustering; Adaptation models; Clustering algorithms; Complexity theory; Data models; Internet; Web mining; clustering; data structures; database applications; database management; graphs and networks; information search and retrieval; mining methods and algorithms; pattern recognition;
Journal_Title :
Internet Computing, IEEE
DOI :
10.1109/MIC.2012.141
