Paulo Shakarian, Ph.D.
Affiliations: | 2011 | Computer Science | University of Maryland, College Park, College Park, MD |
Area:
Artificial Intelligence,Computer SystemsGoogle:
"Paulo Shakarian"Parents
Sign in to add mentorV. S. Subrahmanian | grad student | 2011 | University of Maryland | |
(Spatio-termporal reasoning about agent behavior.) |
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Publications
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Sarkar S, Almukaynizi M, Shakarian J, et al. (2019) Mining user interaction patterns in the darkweb to predict enterprise cyber incidents Social Network Analysis and Mining. 9: 57 |
Sarkar S, Guo R, Shakarian P. (2019) Using network motifs to characterize temporal network evolution leading to diffusion inhibition Social Network Analysis and Mining. 9: 14 |
Sarkar S, Guo R, Shakarian P. (2017) Understanding and forecasting lifecycle events in information cascades Social Network Analysis and Mining. 7: 55 |
Guo R, Shaabani E, Bhatnagar A, et al. (2016) Toward early and order-of-magnitude cascade prediction in social networks Social Network Analysis and Mining. 6 |
Simari GI, Shakarian P, Falappa MA. (2016) A quantitative approach to belief revision in structured probabilistic argumentation Annals of Mathematics and Artificial Intelligence. 76: 375-408 |
Chen X, Candan KS, Sapino ML, et al. (2015) KSGM: Keynode-driven scalable graph matching International Conference On Information and Knowledge Management, Proceedings. 19: 1101-1110 |
Shakarian P, Simari GI, Moores G, et al. (2015) Belief revision in structured probabilistic argumentation: Model and application to cyber security Annals of Mathematics and Artificial Intelligence |
Shakarian P, Simari GI, Moores G, et al. (2015) Cyber attribution: An argumentation-based approach Advances in Information Security. 56: 151-171 |
Moores G, Shakarian P, Macdonald B, et al. (2014) Finding near-optimal groups of epidemic spreaders in a complex network. Plos One. 9: e90303 |
Shakarian P, Simari GI, Falappa MA. (2014) Belief revision in structured probabilistic argumentation Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8367: 324-343 |