The Journal of Machine Learning Research
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
HSN-PAM: Finding Hierarchical Probabilistic Groups from Large-Scale Networks
ICDMW '07 Proceedings of the Seventh IEEE International Conference on Data Mining Workshops
SFCS '88 Proceedings of the 29th Annual Symposium on Foundations of Computer Science
On the leakage of personally identifiable information via online social networks
Proceedings of the 2nd ACM workshop on Online social networks
Probabilistic community discovery using hierarchical latent Gaussian mixture model
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Latent dirichlet allocation for tag recommendation
Proceedings of the third ACM conference on Recommender systems
Empirical comparison of algorithms for network community detection
Proceedings of the 19th international conference on World wide web
PLDA+: Parallel latent dirichlet allocation with data placement and pipeline processing
ACM Transactions on Intelligent Systems and Technology (TIST)
Incremental web-site boundary detection using random walks
MLDM'11 Proceedings of the 7th international conference on Machine learning and data mining in pattern recognition
Using content and interactions for discovering communities in social networks
Proceedings of the 21st international conference on World Wide Web
Mining longitudinal network for predicting company value
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Integrating community matching and outlier detection for mining evolutionary community outliers
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Event-based social networks: linking the online and offline social worlds
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
How Multimedia in Enterprise Social Networks Matters to People's Performance
ICMEW '12 Proceedings of the 2012 IEEE International Conference on Multimedia and Expo Workshops
Content independent metadata production as a machine learning problem
MLDM'12 Proceedings of the 8th international conference on Machine Learning and Data Mining in Pattern Recognition
Discovering K web user groups with specific aspect interests
MLDM'12 Proceedings of the 8th international conference on Machine Learning and Data Mining in Pattern Recognition
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This paper tackles the problem of detecting topical communities from within an organization by mining readily available network access pattern information. A Bayesian generative process is used to model the behavior of user's network access pattern and thereby her consumption of online content. The idea is that users within same topical interest group tend to share similar online access patterns. By leveraging this pattern, along with side information of domain-names and keywords within the accessed websites, one is able to model these observations under the framework of a mixed membership statistical model. Hence the access patterns of users-to-websites, as measured at the edge of an organization's network boundary, can be decomposed into constituent topical communities without any human effort in selecting specific features. Experimental results on real-world network flow trace demonstrate that the proposed method can effectively detect topically meaningful community structures. Besides better detection accuracy of communities compared with other community detection methods, the proposed method can detect interesting but non-evident hidden communities which cannot readily be detected by other known methods.