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IEEE Computer Society, 2012.
[2] N. Aston and W. Hu. Community detection in dynamic social networks. Communications and Network, page 124, 2014.
[3] S. Baluja, R. Seth, D Sivakumar, Y. Jing, J. Yagnik, S. Kumar, D. Ravichandran, and M. Aly. Video suggestion and discovery for YouTube: taking random walks through the view graph. In Proceedings of the 17th international
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Proceedings of the Tenth International Workshop on Artificial Intelligence and
Statistics, pages 17–24, 2005.
[6] Y Bengio, O Delalleau, and NL Roux. Label propagation and quadratic criterion. In Semi-Supervised Learning. MIT Press, 2007.
[7] A. Blum and S. Chawla. Learning from labeled and unlabeled data using
graph mincuts. In Proceedings of the 18th International Conference on Machine Learning, ICML ’01, pages 19–26, 2001.
[8] A. Blum, J. Lafferty, M.R. Rwebangira, and R. Reddy. Semi-supervised learning using randomized mincuts. In Proceedings on the 21st international conference on Machine learning. ACM Press, 2004.
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199
[1] P. Anchuri and M. Magdon-Ismail. Communities and balance in signed networks: A spectral approach. In Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining, pages 235–242.
IEEE Computer Society, 2012.
[2] N. Aston and W. Hu. Community detection in dynamic social networks. Communications and Network, page 124, 2014.
[3] S. Baluja, R. Seth, D Sivakumar, Y. Jing, J. Yagnik, S. Kumar, D. Ravichandran, and M. Aly. Video suggestion and discovery for YouTube: taking random walks through the view graph. In Proceedings of the 17th international
conference on World Wide Web, pages 895–904. ACM, 2008.
[4] M. Belkin, I. Matveeva, and P. Niyogi. Regularization and semi-supervised
learning on large graphs. Learning Theory, pages 624–638, 2004.
[5] M. Belkin, P. Niyogi, and V. Sindhwani. On manifold regularization. In
Proceedings of the Tenth International Workshop on Artificial Intelligence and
Statistics, pages 17–24, 2005.
[6] Y Bengio, O Delalleau, and NL Roux. Label propagation and quadratic criterion. In Semi-Supervised Learning. MIT Press, 2007.
[7] A. Blum and S. Chawla. Learning from labeled and unlabeled data using
graph mincuts. In Proceedings of the 18th International Conference on Machine Learning, ICML ’01, pages 19–26, 2001.
[8] A. Blum, J. Lafferty, M.R. Rwebangira, and R. Reddy. Semi-supervised learning using randomized mincuts. In Proceedings on the 21st international conference on Machine learning. ACM Press, 2004.
[9] A. Bouchachia and M. Prossegger. Incremental spectral clustering. Learning
in Non-Stationary Environments: Methods and Applications, page 77, 2012.
[10] T. B¨ uhler and M. Hein. Spectral clustering based on the graph p-Laplacian. In
Proceedings of the 26th Annual International Conference on Machine Learning, pages 81–88. ACM, 2009.
199