Graph based anomaly detection and description: a survey L Akoglu, H Tong, D Koutra Data mining and knowledge discovery 29, 626-688, 2015 | 1656 | 2015 |
Beyond homophily in graph neural networks: Current limitations and effective designs J Zhu, Y Yan, L Zhao, M Heimann, L Akoglu, D Koutra Advances in neural information processing systems 33, 7793-7804, 2020 | 828 | 2020 |
Oddball: Spotting anomalies in weighted graphs L Akoglu, M McGlohon, C Faloutsos Advances in Knowledge Discovery and Data Mining: 14th Pacific-Asia …, 2010 | 750 | 2010 |
Collective opinion spam detection: Bridging review networks and metadata S Rayana, L Akoglu Proceedings of the 21th acm sigkdd international conference on knowledge …, 2015 | 650 | 2015 |
Opinion fraud detection in online reviews by network effects L Akoglu, R Chandy, C Faloutsos Proceedings of the international AAAI conference on web and social media 7 …, 2013 | 560 | 2013 |
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 | 556 | 2012 |
Pairnorm: Tackling oversmoothing in gnns L Zhao, L Akoglu arXiv preprint arXiv:1909.12223, 2019 | 538 | 2019 |
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 | 502 | 2015 |
A comprehensive survey on graph anomaly detection with deep learning X Ma, J Wu, S Xue, J Yang, C Zhou, QZ Sheng, H Xiong, L Akoglu IEEE Transactions on Knowledge and Data Engineering 35 (12), 12012-12038, 2021 | 491 | 2021 |
Focused clustering and outlier detection in large attributed graphs B Perozzi, L Akoglu, P Iglesias Sánchez, E Müller Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 285 | 2014 |
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 | 277 | 2011 |
Fast memory-efficient anomaly detection in streaming heterogeneous graphs E Manzoor, SM Milajerdi, L Akoglu Proceedings of the 22nd ACM SIGKDD international conference on knowledge …, 2016 | 251 | 2016 |
Discovering opinion spammer groups by network footprints J Ye, L Akoglu Machine Learning and Knowledge Discovery in Databases: European Conference …, 2015 | 199 | 2015 |
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, 2017 | 194 | 2017 |
Event detection in time series of mobile communication graphs L Akoglu, C Faloutsos Army science conference 1, 141, 2010 | 186 | 2010 |
Pics: Parameter-free identification of cohesive subgroups in large attributed graphs L Akoglu, H Tong, B Meeder, C Faloutsos Proceedings of the 2012 SIAM international conference on data mining, 439-450, 2012 | 172 | 2012 |
Weighted graphs and disconnected components: patterns and a generator M McGlohon, L Akoglu, C Faloutsos Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008 | 167 | 2008 |
Scalable anomaly ranking of attributed neighborhoods B Perozzi, L Akoglu Proceedings of the 2016 SIAM International Conference on Data Mining, 207-215, 2016 | 166 | 2016 |
Less is more: Building selective anomaly ensembles S Rayana, L Akoglu Acm transactions on knowledge discovery from data (tkdd) 10 (4), 1-33, 2016 | 162 | 2016 |
Fast and reliable anomaly detection in categorical data L Akoglu, H Tong, J Vreeken, C Faloutsos Proceedings of the 21st ACM international conference on Information and …, 2012 | 159 | 2012 |