| Collective classification in network data P Sen, G Namata, M Bilgic, L Getoor, B Galligher, T Eliassi-Rad AI magazine 29 (3), 93-93, 2008 | 1023 | 2008 |
| Fast best-effort pattern matching in large attributed graphs H Tong, C Faloutsos, C Faloutsos, B Gallagher, T Eliassi-Rad Proceedings of the 13th ACM SIGKDD international conference on Knowledge …, 2007 | 257 | 2007 |
| Rolx: structural role extraction & mining in large graphs K Henderson, B Gallagher, T Eliassi-Rad, H Tong, S Basu, L Akoglu, ... Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012 | 235 | 2012 |
| Visual analysis of large heterogeneous social networks by semantic and structural abstraction Z Shen, KL Ma, T Eliassi-Rad IEEE transactions on visualization and computer graphics 12 (6), 1427-1439, 2006 | 206 | 2006 |
| Using ghost edges for classification in sparsely labeled networks B Gallagher, H Tong, T Eliassi-Rad, C Faloutsos Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008 | 164 | 2008 |
| Gelling, and melting, large graphs by edge manipulation H Tong, BA Prakash, T Eliassi-Rad, M Faloutsos, C Faloutsos Proceedings of the 21st ACM international conference on Information and …, 2012 | 160 | 2012 |
| APATE: A novel approach for automated credit card transaction fraud detection using network-based extensions V Van Vlasselaer, C Bravo, O Caelen, T Eliassi-Rad, L Akoglu, M Snoeck, ... Decision Support Systems 75, 38-48, 2015 | 145 | 2015 |
| It's who you know: graph mining using recursive structural features K Henderson, B Gallagher, L Li, L Akoglu, T Eliassi-Rad, H Tong, ... Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 142 | 2011 |
| On the vulnerability of large graphs H Tong, BA Prakash, C Tsourakakis, T Eliassi-Rad, C Faloutsos, ... 2010 IEEE International Conference on Data Mining, 1091-1096, 2010 | 128 | 2010 |
| A probabilistic model for using social networks in personalized item recommendation AJB Chaney, DM Blei, T Eliassi-Rad Proceedings of the 9th ACM Conference on Recommender Systems, 43-50, 2015 | 117 | 2015 |
| Applying latent dirichlet allocation to group discovery in large graphs K Henderson, T Eliassi-Rad Proceedings of the 2009 ACM symposium on Applied Computing, 1456-1461, 2009 | 83 | 2009 |
| Netsimile: A scalable approach to size-independent network similarity M Berlingerio, D Koutra, T Eliassi-Rad, C Faloutsos arXiv preprint arXiv:1209.2684, 2012 | 65 | 2012 |
| Measuring tie strength in implicit social networks M Gupte, T Eliassi-Rad Proceedings of the 4th Annual ACM Web Science Conference, 109-118, 2012 | 61 | 2012 |
| Metric forensics: a multi-level approach for mining volatile graphs K Henderson, T Eliassi-Rad, C Faloutsos, L Akoglu, L Li, K Maruhashi, ... Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010 | 60 | 2010 |
| HCDF: A hybrid community discovery framework K Henderson, T Eliassi-Rad, S Papadimitriou, C Faloutsos Proceedings of the 2010 SIAM International Conference on Data Mining, 754-765, 2010 | 58 | 2010 |
| A system for building intelligent agents that learn to retrieve and extract information T Eliassi-Rad, J Shavlik User Modeling and User-Adapted Interaction 13 (1-2), 35-88, 2003 | 57 | 2003 |
| Gotcha! Network-based fraud detection for social security fraud V Van Vlasselaer, T Eliassi-Rad, L Akoglu, M Snoeck, B Baesens Management Science 63 (9), 3090-3110, 2016 | 56 | 2016 |
| Graphite: A visual query system for large graphs DH Chau, C Faloutsos, H Tong, JI Hong, B Gallagher, T Eliassi-Rad 2008 IEEE International Conference on Data Mining Workshops, 963-966, 2008 | 55 | 2008 |
| Leveraging label-independent features for classification in sparsely labeled networks: An empirical study B Gallagher, T Eliassi-Rad International Workshop on Social Network Mining and Analysis, 1-19, 2008 | 55 | 2008 |
| Network similarity via multiple social theories M Berlingerio, D Koutra, T Eliassi-Rad, C Faloutsos Proceedings of the 2013 IEEE/ACM International Conference on Advances in …, 2013 | 54 | 2013 |
Brian GallagherComputer Scientist, Lawrence Livermore National LaboratoryEmail verificata su llnl.gov