@inproceedings{cornelilatoucheetal2015asonam,
 author = {Corneli, Marco and Latouche, Pierre and Rossi, Fabrice},
 title = {Modelling Time Evolving Interactions in Networks Through a Non Stationary Extension of Stochastic Block Models},
 booktitle = {Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2015)},
 year = {2015},
 isbn = {978-1-4503-3854-7},
 address = {Paris, France},
 pages = {1590--1591},
 numpages = {2},
 publisherlink = {http://doi.acm.org/10.1145/2808797.2809348},
 doi = {10.1145/2808797.2809348},
 acmid = {2809348},
 publisher = {ACM},
month={8},
 publisheraddress = {New York, NY, USA},
    entrysubtype={inproceedings-international-conference},
    language = {english},
    audience = {international},
   abstract={The stochastic block model (SBM) describes interactions between nodes 
of a network following a probabilistic approach. Nodes belong
to hidden clusters and the probabilities of interactions only depend 
on these clusters. Interactions of 
time varying intensity are not taken into account.
By partitioning 
the whole time horizon, in which interactions are observed, 
we develop a non stationary extension of the SBM,
allowing us to simultaneously cluster the nodes of a network and 
the fixed time intervals in which interactions take place. The number 
of clusters as well as memberships to 
clusters are finally obtained through the maximization of 
the complete-data integrated likelihood 
relying on a greedy search approach. Experiments are carried
out in order to assess the proposed methodology.},
editors={Pei, Jian and Silvestri, Fabrizio and Tang, Jie},
hal={hal-01263540},
}