TY - GEN
T1 - Online community transition detection
AU - Tan, Biying
AU - Zhu, Feida
AU - Qu, Qiang
AU - Liu, Siyuan
PY - 2014
Y1 - 2014
N2 - Mining user behavior patterns in social networks is of great importance in user behavior analysis, targeted marketing, churn prediction and other applications. However, less effort has been made to study the evolution of user behavior in social communities. In particular, users join and leave communities over time. How to automatically detect the online community transitions of individual users is a research problem of immense practical value yet with great technical challenges. In this paper, we propose an algorithm based on the Minimum Description Length (MDL) principle to trace the evolution of community transition of individual users, adaptive to the noisy behavior. Experiments on real data sets demonstrate the efficiency and effectiveness of our proposed method.
AB - Mining user behavior patterns in social networks is of great importance in user behavior analysis, targeted marketing, churn prediction and other applications. However, less effort has been made to study the evolution of user behavior in social communities. In particular, users join and leave communities over time. How to automatically detect the online community transitions of individual users is a research problem of immense practical value yet with great technical challenges. In this paper, we propose an algorithm based on the Minimum Description Length (MDL) principle to trace the evolution of community transition of individual users, adaptive to the noisy behavior. Experiments on real data sets demonstrate the efficiency and effectiveness of our proposed method.
UR - http://www.scopus.com/inward/record.url?scp=84958547398&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84958547398&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-08010-9_68
DO - 10.1007/978-3-319-08010-9_68
M3 - Conference contribution
AN - SCOPUS:84958547398
SN - 9783319080093
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 633
EP - 644
BT - Web-Age Information Management - 15th International Conference, WAIM 2014, Proceedings
PB - Springer Verlag
T2 - 15th International Conference on Web-Age Information Management, WAIM 2014
Y2 - 16 June 2014 through 18 June 2014
ER -