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ORCIDMoshe Unger
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2020 – today
- 2024
[j6]Moshe Unger
, Michel Wedel, Alexander Tuzhilin:
Predicting consumer choice from raw eye-movement data using the RETINA deep learning architecture. Data Min. Knowl. Discov. 38(3): 1069-1100 (2024)- [c13]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Alexander Tuzhilin, Moshe Unger:
Workshop on Context-Aware Recommender Systems (CARS) 2024. RecSys 2024: 1219-1221 - 2023
- [j5]Moshe Unger, Pan Li, Sahana (Shahana) Sen, Alexander Tuzhilin:
Don't Need All Eggs in One Basket: Reconstructing Composite Embeddings of Customers from Individual-Domain Embeddings. ACM Trans. Manag. Inf. Syst. 14(2): 20:1-20:30 (2023) - [c12]Moshe Unger, Alexander Tuzhilin:
Hierarchical Contextual Embeddings for Context-Aware Recommendations (Extended Abstract). ICDE 2023: 3863-3864 - [c11]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Alexander Tuzhilin, Moshe Unger:
Workshop on Context-Aware Recommender Systems 2023. RecSys 2023: 1234-1236 - 2022
- [j4]Moshe Unger, Alexander Tuzhilin:
Hierarchical Latent Context Representation for Context-Aware Recommendations. IEEE Trans. Knowl. Data Eng. 34(7): 3322-3334 (2022) - [c10]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger:
CARS: Workshop on Context-Aware Recommender Systems 2022. RecSys 2022: 691-693 - [r1]Gediminas Adomavicius, Konstantin Bauman, Alexander Tuzhilin, Moshe Unger:
Context-Aware Recommender Systems: From Foundations to Recent Developments. Recommender Systems Handbook 2022: 211-250 - 2021
- [c9]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger:
Workshop on Context-Aware Recommender Systems (CARS) 2021. RecSys 2021: 813-814 - 2020
- [j3]Moshe Unger, Alexander Tuzhilin, Amit Livne:
Context-Aware Recommendations Based on Deep Learning Frameworks. ACM Trans. Manag. Inf. Syst. 11(2): 8:1-8:15 (2020) - [c8]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger:
Workshop on Context-Aware Recommender Systems. RecSys 2020: 635-637 - [i2]Sigal Shaked, Amos Zamir, Roman Vainshtein, Moshe Unger, Lior Rokach, Rami Puzis, Bracha Shapira:
Sequence Preserving Network Traffic Generation. CoRR abs/2002.09832 (2020)
2010 – 2019
- 2019
- [c7]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger:
Workshop on context-aware recommender systems. RecSys 2019: 548-549 - [i1]Amit Livne, Moshe Unger, Bracha Shapira, Lior Rokach:
Deep Context-Aware Recommender System Utilizing Sequential Latent Context. CoRR abs/1909.03999 (2019) - 2018
- [j2]Moshe Unger, Bracha Shapira, Lior Rokach, Amit Livne:
Inferring contextual preferences using deep encoder-decoder learners. New Rev. Hypermedia Multim. 24(3): 262-290 (2018) - 2017
- [c6]Moshe Unger, Bracha Shapira, Lior Rokach, Ariel Bar:
Inferring Contextual Preferences Using Deep Auto-Encoding. UMAP 2017: 221-229 - 2016
- [j1]Moshe Unger, Ariel Bar, Bracha Shapira, Lior Rokach:
Towards latent context-aware recommendation systems. Knowl. Based Syst. 104: 165-178 (2016) - [c5]Ariel Bar, Bracha Shapira, Lior Rokach, Moshe Unger:
Scalable attack propagation model and algorithms for honeypot systems. IEEE BigData 2016: 1130-1135 - [c4]Moshe Unger, Bracha Shapira, Lior Rokach, Ariel Bar:
Deep Auto-Encoding for Context-Aware Inference of Preferred Items' Categories. RecSys Posters 2016 - [c3]Ariel Bar, Bracha Shapira, Lior Rokach, Moshe Unger:
Identifying Attack Propagation Patterns in Honeypots Using Markov Chains Modeling and Complex Networks Analysis. SwSTE 2016: 28-36 - 2015
- [c2]Moshe Unger:
Latent Context-Aware Recommender Systems. RecSys 2015: 383-386 - 2014
- [c1]Moshe Unger, Lior Rokach, Ariel Bar, Ehud Gudes, Bracha Shapira:
Contexto: lessons learned from mobile context inference. UbiComp Adjunct 2014: 175-178
Coauthor Index
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