This paper describes and evaluates privacy-friendly methods for extracting quasi-social networks from browser behavior on user-generated content sites, for the purpose of finding ...
Foster J. Provost, Brian Dalessandro, Rod Hook, Xi...
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
Heterogeneous data co-clustering has attracted more and more attention in recent years due to its high impact on various applications. While the co-clustering algorithms for two t...
Bin Gao, Tie-Yan Liu, Xin Zheng, QianSheng Cheng, ...
Service composition concerns both integration of heterogeneous distributed applications and dynamic selection of services. QoS-aware selection enables a service requester with cer...
Davide Bacciu, Maria Grazia Buscemi, Lusine Mkrtch...
This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...