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Moshe Unger
Moshe Unger
Assistant Professor at Tel Aviv University - Coller School of Management
Bestätigte E-Mail-Adresse bei stern.nyu.edu
Titel
Zitiert von
Zitiert von
Jahr
Towards latent context-aware recommendation systems
M Unger, A Bar, B Shapira, L Rokach
Knowledge-Based Systems 104, 165-178, 2016
1552016
Context-aware recommendations based on deep learning frameworks
M Unger, A Tuzhilin, A Livne
ACM Transactions on Management Information Systems (TMIS) 11 (2), 1-15, 2020
652020
Identifying attack propagation patterns in honeypots using Markov chains modeling and complex networks analysis
A Bar, B Shapira, L Rokach, M Unger
2016 IEEE international conference on software science, technology and …, 2016
432016
Latent context-aware recommender systems
M Unger
Proceedings of the 9th ACM Conference on Recommender Systems, 383-386, 2015
342015
Context-Aware Recommender Systems: From Foundations to Recent DevelopmentsContext-aware recommender systems
G Adomavicius, K Bauman, A Tuzhilin, M Unger
Recommender systems handbook, 211-250, 2021
332021
Inferring contextual preferences using deep auto-encoding
M Unger, B Shapira, L Rokach, A Bar
Proceedings of the 25th Conference on User Modeling, Adaptation and …, 2017
232017
Deep context-aware recommender system utilizing sequential latent context
A Livne, M Unger, B Shapira, L Rokach
arXiv preprint arXiv:1909.03999, 2019
202019
Inferring contextual preferences using deep encoder-decoder learners
M Unger, B Shapira, L Rokach, A Livne
New Review of Hypermedia and Multimedia 24 (3), 262-290, 2018
122018
Hierarchical latent context representation for context-aware recommendations
M Unger, A Tuzhilin
IEEE Transactions on Knowledge and Data Engineering 34 (7), 3322-3334, 2020
112020
Scalable attack propagation model and algorithms for honeypot systems
A Bar, B Shapira, L Rokach, M Unger
2016 IEEE International Conference on Big Data (Big Data), 1130-1135, 2016
102016
Contexto: lessons learned from mobile context inference
M Unger, A Bar, B Shapira, L Rokach, E Gudes
Proceedings of the 2014 ACM International Joint Conference on Pervasive and …, 2014
62014
Workshop on context-aware recommender systems
G Adomavicius, K Bauman, B Mobasher, F Ricci, A Tuzhilin, M Unger
Proceedings of the 14th ACM Conference on Recommender Systems, 635-637, 2020
42020
Deep multi-objective multi-stakeholder music recommendation
M Unger, P Li, MC Cohen, B Brost, A Tuzhilin
NYU Stern School of Business Forthcoming, 2021
32021
Deep Auto-Encoding for Context-Aware Inference of Preferred Items' Categories.
M Unger, B Shapira, L Rokach, A Bar
RecSys Posters, 2016
32016
Predicting consumer choice from raw eye-movement data using the RETINA deep learning architecture
M Unger, M Wedel, A Tuzhilin
Data Mining and Knowledge Discovery 38 (3), 1069-1100, 2024
22024
Hierarchical Latent Context Representation for CARS
M Unger, A Tuzhilin
Stern School of Business, New York University, 2019
22019
Don’t Need All Eggs in One Basket: Reconstructing Composite Embeddings of Customers from Individual-Domain Embeddings
M Unger, P Li, S Sen, A Tuzhilin
ACM Transactions on Management Information Systems 14 (2), 1-30, 2023
12023
Sequence preserving network traffic generation
S Shaked, A Zamir, R Vainshtein, M Unger, L Rokach, R Puzis, B Shapira
arXiv preprint arXiv:2002.09832, 2020
12020
Workshop on Context-Aware Recommender Systems 2023
G Adomavicius, K Bauman, B Mobasher, A Tuzhilin, M Unger
Proceedings of the 17th ACM Conference on Recommender Systems, 1234-1236, 2023
2023
Hierarchical Contextual Embeddings for Context-Aware Recommendations
M Unger, A Tuzhilin
2023 IEEE 39th International Conference on Data Engineering (ICDE), 3863-3864, 2023
2023
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