Collective classification in network data P Sen, G Namata, M Bilgic, L Getoor, B Gallagher, T Eliassi-Rad AI magazine 29 (3), 93, 2008 | 4226 | 2008 |
Maxprop: Routing for vehicle-based disruption-tolerant networks J Burgess, B Gallagher, D Jensen, BN Levine INFOCOM 2006. 25th IEEE International Conference on Computer Communications …, 2006 | 2914 | 2006 |
RolX: Structural Role Extraction & Mining in Large Graphs K Henderson, B Gallagher, T Eliassi-Rad, H Tong, S Basu, ... | 587 | 2012 |
Why collective inference improves relational classification D Jensen, J Neville, B Gallagher Proceedings of the tenth ACM SIGKDD international conference on Knowledge …, 2004 | 371 | 2004 |
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 | 359* | 2011 |
Fast best-effort pattern matching in large attributed graphs H Tong, C Faloutsos, B Gallagher, T Eliassi-Rad Proceedings of the 13th ACM SIGKDD international conference on Knowledge …, 2007 | 341 | 2007 |
Matching Structure and Semantics: A Survey on Graph-Based Pattern Matching. B Gallagher AAAI Fall Symposium: Capturing and Using Patterns for Evidence Detection 45, 2006 | 297 | 2006 |
Modeling dynamic behavior in large evolving graphs RA Rossi, B Gallagher, J Neville, K Henderson Proceedings of the sixth ACM international conference on Web search and data …, 2013 | 249 | 2013 |
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 | 207 | 2008 |
TimeCrunch: Interpretable Dynamic Graph Summarization N Shah, D Koutra, T Zou, B Gallagher, C Faloutsos Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015 | 177 | 2015 |
DeltaCon Principled Massive-Graph Similarity Function with Attribution D Koutra, N Shah, JT Vogelstein, B Gallagher, C Faloutsos ACM Transactions on Knowledge Discovery from Data (TKDD) 10 (3), 1-43, 2016 | 160 | 2016 |
Network structure inference, a survey: Motivations, methods, and applications I Brugere, B Gallagher, TY Berger-Wolf ACM Computing Surveys (CSUR) 51 (2), 1-39, 2018 | 158 | 2018 |
Attributed graph models: modeling network structure with correlated attributes JJ Pfeiffer III, S Moreno, T La Fond, J Neville, B Gallagher Proceedings of the 23rd international conference on World wide web, 831-842, 2014 | 154 | 2014 |
Simple estimators for relational bayesian classifiers J Neville, D Jensen, B Gallagher Third IEEE International Conference on Data Mining, 609-612, 2003 | 152 | 2003 |
Reliable and explainable machine-learning methods for accelerated material discovery B Kailkhura, B Gallagher, S Kim, A Hiszpanski, TYJ Han npj Computational Materials 5 (1), 108, 2019 | 144 | 2019 |
Spotting suspicious link behavior with fbox: An adversarial perspective N Shah, A Beutel, B Gallagher, C Faloutsos 2014 IEEE International Conference on Data Mining, 959-964, 2014 | 132 | 2014 |
Leveraging label-independent features for classification in sparsely labeled networks: An empirical study B Gallagher, T Eliassi-Rad Advances in Social Network Mining and Analysis, 1-19, 2010 | 89 | 2010 |
Explainable machine learning in materials science X Zhong, B Gallagher, S Liu, B Kailkhura, A Hiszpanski, TYJ Han npj Computational Materials 8 (1), 204, 2022 | 85 | 2022 |
A Guide to Selecting a Network Similarity Method S Soundarajan, T Eliassi-Rad, B Gallagher | 82 | 2014 |
Exploiting relational structure to understand publication patterns in high-energy physics A McGovern, L Friedland, M Hay, B Gallagher, A Fast, J Neville, D Jensen ACM SIGKDD Explorations Newsletter 5 (2), 165-172, 2003 | 73 | 2003 |