@conference {38, title = {Discovery of Social Groups Using Call Detail Records}, booktitle = {On the Move to Meaningful Internet Systems: OTM 2008 Workshops}, year = {2008}, month = {11/2008}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, address = {Monterrey, Mexico}, abstract = {

In this paper we propose the affinity model for classifying social groups based on mobile phone call detail records. We use affinity to measure the similarity between probability distributions. Since phone calls are stochastic process, it makes more sense to use probability affinity to classify the social groups. This work is useful for enhancing homeland security, detecting unwanted calls (e.g., spam) and product marketing. For validation of our results, we used actual call logs of 100 users collected at MIT by the Reality Mining Project group for a period of 8 months. The experimental results show that our model achieves good performance with high accuracy.

}, isbn = {978-3-540-88875-8}, doi = {10.1007/978-3-540-88875-8_72}, url = {http://dx.doi.org/10.1007/978-3-540-88875-8_72}, author = {Zhang, Huiqi and Ram Dantu}, editor = {Meersman, Robert and Tari, Zahir and Herrero, Pilar} } @inbook {12, title = {Group Recommendation System for Facebook}, booktitle = {On the Move to Meaningful Internet Systems: OTM 2008 Workshops, Monterrey, Mexico, November 9-14, 2008. Proceedings}, year = {2008}, pages = {211{\textendash}219}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, address = {Berlin, Heidelberg}, abstract = {

Online social networking has become a part of our everyday lives, and one of the popular online social network (SN) sites on the Internet is Facebook, where users communicate with their friends, join to groups, create groups, play games, and make friends around the world. Also, the vast number of groups are created for different causes and beliefs. However, overwhelming number of groups in one category causes difficulties for users to select a right group to join. To solve this problem, we introduce group recommendation system (GRS) using combination of hierarchical clustering technique and decision tree. We believe that Facebook SN groups can be identified based on their members{\textquoteright} profiles. Number of experiment results showed that GRS can make 73\% accurate recommendation.

}, keywords = {decision tree, recommendation system, Social network}, isbn = {978-3-540-88875-8}, doi = {10.1007/978-3-540-88875-8_41}, url = {http://dx.doi.org/10.1007/978-3-540-88875-8_41}, author = {Baatarjav, Enkh-Amgalan and Phithakkitnukoon, Santi and Ram Dantu}, editor = {Meersman, Robert and Tari, Zahir and Herrero, Pilar} } @conference {49, title = {Inferring Social Groups Using Call Logs}, booktitle = {On the Move to Meaningful Internet Systems: OTM 2008 Workshops}, year = {2008}, month = {11/2008}, pages = {200{\textendash}210}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, address = {Monterrey, Mexico}, abstract = {

Recent increase in population of mobile phone users makes it a valuable source of information for social network analysis. For a given call log, how much can we tell about the person{\textquoteright}s social group? Unnoticeably, phone user{\textquoteright}s calling personality and habit has been concealed in the call logs from which we believe that it can be extracted to infer its user{\textquoteright}s social group information. In this paper, we present an end-to-end system for inferring social networks based on {\textquotedblleft}only{\textquotedblright} call logs using kernel-based na{\"\i}ve Bayesian learning. We also introduce normalized mutual information for feature selection process. Our model is evaluated with real-life call logs where it performs at high accuracy rate of 81.82\%.

}, isbn = {978-3-540-88875-8}, doi = {10.1007/978-3-540-88875-8_40}, url = {http://dx.doi.org/10.1007/978-3-540-88875-8_40}, author = {Phithakkitnukoon, Santi and Ram Dantu}, editor = {Meersman, Robert and Tari, Zahir and Herrero, Pilar} }