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ORCIDAlexander Tuzhilin
Alex Tuzhilin
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- affiliation: New York University, USA
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2020 – today
- 2024
[j62]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)- [j61]Pan Li, Alexander Tuzhilin:
When Variety Seeking Meets Unexpectedness: Incorporating Variety-Seeking Behaviors into Design of Unexpected Recommender Systems. Inf. Syst. Res. 35(3): 1257-1273 (2024) - [j60]Pan Li, Maofei Que, Alexander Tuzhilin:
Dual Contrastive Learning for Efficient Static Feature Representation in Sequential Recommendations. IEEE Trans. Knowl. Data Eng. 36(2): 544-555 (2024) - [c76]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Alexander Tuzhilin, Moshe Unger:
Workshop on Context-Aware Recommender Systems (CARS) 2024. RecSys 2024: 1219-1221 - [c75]Konstantin Bauman, Alexey Vasilev, Alexander Tuzhilin:
Does the Long Tail of Context Exist and Matter? The Case of Dialogue-based Recommender Systems. UMAP 2024: 273-278 - [i22]Pan Li, Alexander Tuzhilin:
Deep Pareto Reinforcement Learning for Multi-Objective Recommender Systems. CoRR abs/2407.03580 (2024) - 2023
- [j59]Pan Li, Brian Brost, Alexander Tuzhilin:
Adversarial Learning for Cross Domain Recommendations. ACM Trans. Intell. Syst. Technol. 14(1): 5:1-5:25 (2023) - [j58]Pan Li, Alexander Tuzhilin:
Dual Metric Learning for Effective and Efficient Cross-Domain Recommendations. IEEE Trans. Knowl. Data Eng. 35(1): 321-334 (2023) - [j57]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) - [c74]Moshe Unger, Alexander Tuzhilin:
Hierarchical Contextual Embeddings for Context-Aware Recommendations (Extended Abstract). ICDE 2023: 3863-3864 - [c73]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Alexander Tuzhilin, Moshe Unger:
Workshop on Context-Aware Recommender Systems 2023. RecSys 2023: 1234-1236 - 2022
- [j56]Konstantin Bauman, Alexander Tuzhilin:
Know Thy Context: Parsing Contextual Information from User Reviews for Recommendation Purposes. Inf. Syst. Res. 33(1): 179-202 (2022) - [j55]Panagiotis Adamopoulos, Anindya Ghose, Alexander Tuzhilin:
Heterogeneous Demand Effects of Recommendation Strategies in a Mobile Application: Evidence from Econometric Models and Machine-Learning Instruments. MIS Q. 46(1): 101-150 (2022) - [j54]Moshe Unger, Alexander Tuzhilin:
Hierarchical Latent Context Representation for Context-Aware Recommendations. IEEE Trans. Knowl. Data Eng. 34(7): 3322-3334 (2022) - [j53]Pan Li, Alexander Tuzhilin:
Learning Latent Multi-Criteria Ratings From User Reviews for Recommendations. IEEE Trans. Knowl. Data Eng. 34(8): 3854-3866 (2022) - [c72]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger:
CARS: Workshop on Context-Aware Recommender Systems 2022. RecSys 2022: 691-693 - [c71]Dmitrii Babaev, Nikita Ovsov, Ivan Kireev, Mariya Ivanova, Gleb Gusev, Ivan Nazarov, Alexander Tuzhilin:
CoLES: Contrastive Learning for Event Sequences with Self-Supervision. SIGMOD Conference 2022: 1190-1199 - [r2]Gediminas Adomavicius, Konstantin Bauman, Alexander Tuzhilin, Moshe Unger:
Context-Aware Recommender Systems: From Foundations to Recent Developments. Recommender Systems Handbook 2022: 211-250 - [i21]Konstantin Bauman, Alexey Vasilev, Alexander Tuzhilin:
The Long Tail of Context: Does it Exist and Matter? CoRR abs/2210.01023 (2022) - 2021
- [j52]Yong Ge, Huayu Li, Alexander Tuzhilin:
Route Recommendations for Intelligent Transportation Services. IEEE Trans. Knowl. Data Eng. 33(3): 1169-1182 (2021) - [j51]Manvel Avetisian, Ilya Burenko, Konstantin Egorov, Vladimir Kokh, Aleksandr Nesterov, Aleksandr Nikolaev, Alexander Ponomarchuk, Elena Sokolova, Alex Tuzhilin, Dmitry Umerenkov:
CoRSAI: A System for Robust Interpretation of CT Scans of COVID-19 Patients Using Deep Learning. ACM Trans. Manag. Inf. Syst. 12(4): 28:1-28:16 (2021) - [c70]Konstantin Egorov, Elena Sokolova, Manvel Avetisian, Alexander Tuzhilin:
Noise-resilient Automatic Interpretation of Holter ECG Recordings. BIOSIGNALS 2021: 208-214 - [c69]Pan Li, Zhichao Jiang, Maofei Que, Yao Hu, Alexander Tuzhilin:
Dual Attentive Sequential Learning for Cross-Domain Click-Through Rate Prediction. KDD 2021: 3172-3180 - [c68]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger:
Workshop on Context-Aware Recommender Systems (CARS) 2021. RecSys 2021: 813-814 - [i20]Panagiotis Adamopoulos, Anindya Ghose, Alexander Tuzhilin:
Heterogeneous Demand Effects of Recommendation Strategies in a Mobile Application: Evidence from Econometric Models and Machine-Learning Instruments. CoRR abs/2102.10468 (2021) - [i19]Pan Li, Alexander Tuzhilin:
Dual Metric Learning for Effective and Efficient Cross-Domain Recommendations. CoRR abs/2104.08490 (2021) - [i18]Manvel Avetisian, Ilya Burenko, Konstantin Egorov, Vladimir Kokh, Aleksandr Nesterov, Aleksandr Nikolaev, Alexander Ponomarchuk, Elena Sokolova, Alexander Tuzhilin, Dmitry Umerenkov:
CoRSAI: A System for Robust Interpretation of CT Scans of COVID-19 Patients Using Deep Learning. CoRR abs/2105.11863 (2021) - [i17]Pan Li, Zhichao Jiang, Maofei Que, Yao Hu, Alexander Tuzhilin:
Dual Attentive Sequential Learning for Cross-Domain Click-Through Rate Prediction. CoRR abs/2106.02768 (2021) - [i16]Pan Li, Maofei Que, Zhichao Jiang, Yao Hu, Alexander Tuzhilin:
PURS: Personalized Unexpected Recommender System for Improving User Satisfaction. CoRR abs/2106.02771 (2021) - [i15]Anton Vakhrushev, Alexander Ryzhkov, Maxim Savchenko, Dmitry Simakov, Rinchin Damdinov, Alexander Tuzhilin:
LightAutoML: AutoML Solution for a Large Financial Services Ecosystem. CoRR abs/2109.01528 (2021) - 2020
- [j50]Toine Bogers, Marijn Koolen, Bamshad Mobasher, Casper Petersen, Alexander Tuzhilin:
Report on the fourth workshop on recommendation in complex environments: (ComplexRec 2020). SIGIR Forum 54(2): 12:1-12:7 (2020) - [j49]Pan Li, Alexander Tuzhilin:
Latent Unexpected Recommendations. ACM Trans. Intell. Syst. Technol. 11(6): 70:1-70:25 (2020) - [j48]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) - [c67]Pavel Blinov, Manvel Avetisian, Vladimir Kokh, Dmitry Umerenkov, Alexander Tuzhilin:
Predicting Clinical Diagnosis from Patients Electronic Health Records Using BERT-Based Neural Networks. AIME 2020: 111-121 - [c66]Pan Li, Maofei Que, Zhichao Jiang, Yao Hu, Alexander Tuzhilin:
PURS: Personalized Unexpected Recommender System for Improving User Satisfaction. RecSys 2020: 279-288 - [c65]Leyla Mirvakhabova, Evgeny Frolov, Valentin Khrulkov, Ivan V. Oseledets, Alexander Tuzhilin:
Performance of Hyperbolic Geometry Models on Top-N Recommendation Tasks. RecSys 2020: 527-532 - [c64]Toine Bogers, Marijn Koolen, Casper Petersen, Bamshad Mobasher, Alexander Tuzhilin:
ComplexRec 2020: Workshop on Recommendation in Complex Environments. RecSys 2020: 609-610 - [c63]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger:
Workshop on Context-Aware Recommender Systems. RecSys 2020: 635-637 - [c62]Pan Li, Alexander Tuzhilin:
DDTCDR: Deep Dual Transfer Cross Domain Recommendation. WSDM 2020: 331-339 - [e7]Toine Bogers, Marijn Koolen, Casper Petersen, Bamshad Mobasher, Alexander Tuzhilin, Oren Sar Shalom, Dietmar Jannach, Joseph A. Konstan:
Proceedings of the Workshops on Recommendation in Complex Scenarios and the Impact of Recommender Systems co-located with 14th ACM Conference on Recommender Systems (RecSys 2020), Online, September 25, 2020. CEUR Workshop Proceedings 2697, CEUR-WS.org 2020 [contents] - [i14]Dmitrii Babaev, Ivan Kireev, Nikita Ovsov, Mariya Ivanova, Gleb Gusev, Alexander Tuzhilin:
Event sequence metric learning. CoRR abs/2002.08232 (2020) - [i13]Manvel Avetisian, Vladimir Kokh, Alexander Tuzhilin, Dmitry Umerenkov:
Radiologist-level stroke classification on non-contrast CT scans with Deep U-Net. CoRR abs/2003.14287 (2020) - [i12]Pavel Blinov, Manvel Avetisian, Vladimir Kokh, Dmitry Umerenkov, Alexander Tuzhilin:
Predicting Clinical Diagnosis from Patients Electronic Health Records Using BERT-based Neural Networks. CoRR abs/2007.07562 (2020) - [i11]Pan Li, Alexander Tuzhilin:
Latent Unexpected Recommendations. CoRR abs/2007.13280 (2020) - [i10]Leyla Mirvakhabova, Evgeny Frolov, Valentin Khrulkov, Ivan V. Oseledets, Alexander Tuzhilin:
Performance of Hyperbolic Geometry Models on Top-N Recommendation Tasks. CoRR abs/2008.06716 (2020) - [i9]Konstantin Egorov, Elena Sokolova, Manvel Avetisian, Alexander Tuzhilin:
Noise-Resilient Automatic Interpretation of Holter ECG Recordings. CoRR abs/2011.09303 (2020)
2010 – 2019
- 2019
- [j47]Michele Gorgoglione, Umberto Panniello, Alexander Tuzhilin:
Recommendation strategies in personalization applications. Inf. Manag. 56(6) (2019) - [c61]Pan Li, Alexander Tuzhilin:
Towards Controllable and Personalized Review Generation. EMNLP/IJCNLP (1) 2019: 3235-3243 - [c60]Dmitrii Babaev, Maxim Savchenko, Alexander Tuzhilin, Dmitrii Umerenkov:
E.T.-RNN: Applying Deep Learning to Credit Loan Applications. KDD 2019: 2183-2190 - [c59]Manvel Avetisian, Vladimir Kokh, Alexander Tuzhilin, Dmitry Umerenkov:
Radiologist-Level Stroke Classification on Non-contrast CT Scans with Deep U-Net. MICCAI (3) 2019: 820-828 - [c58]Marijn Koolen, Toine Bogers, Bamshad Mobasher, Alexander Tuzhilin:
Overview of the Workshop on Recommendation in Complex Scenarios 2019 (ComplexRec 2019). ComplexRec@RecSys 2019: 1-3 - [c57]Pan Li, Alexander Tuzhilin:
Latent Modeling of Unexpectedness for Recommendations. RecSys (Late-Breaking Results) 2019: 36-40 - [c56]Pan Li, Alexander Tuzhilin:
Latent multi-criteria ratings for recommendations. RecSys 2019: 428-431 - [c55]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger:
Workshop on context-aware recommender systems. RecSys 2019: 548-549 - [c54]Marijn Koolen, Toine Bogers, Bamshad Mobasher, Alexander Tuzhilin:
Third workshop on recommendation in complex scenarios (ComplexRec 2019). RecSys 2019: 550-551 - [e6]Marijn Koolen, Toine Bogers, Bamshad Mobasher, Alexander Tuzhilin:
Proceedings of the Workshop on Recommendation in Complex Scenarios co-located with 13th ACM Conference on Recommender Systems (RecSys 2019), Copenhagen, Denmark, September 20, 2019. CEUR Workshop Proceedings 2449, CEUR-WS.org 2019 [contents] - [i8]Pan Li, Alexander Tuzhilin:
Latent Unexpected and Useful Recommendation. CoRR abs/1905.01546 (2019) - [i7]Pan Li, Alexander Tuzhilin:
Latent Multi-Criteria Ratings for Recommendations. CoRR abs/1906.10948 (2019) - [i6]Pan Li, Alexander Tuzhilin:
Towards Controllable and Personalized Review Generation. CoRR abs/1910.03506 (2019) - [i5]Pan Li, Alexander Tuzhilin:
DDTCDR: Deep Dual Transfer Cross Domain Recommendation. CoRR abs/1910.05189 (2019) - [i4]Dmitrii Babaev, Maxim Savchenko, Alexander Tuzhilin, Dmitrii Umerenkov:
E.T.-RNN: Applying Deep Learning to Credit Loan Applications. CoRR abs/1911.02496 (2019) - 2018
- [j46]Konstantin Bauman, Alexander Tuzhilin:
Recommending Remedial Learning Materials to Students by Filling Their Knowledge Gaps. MIS Q. 42(1) (2018) - [i3]Yaroslav Zharov, Denis Korzhenkov, Pavel Shvechikov, Alexander Tuzhilin:
YASENN: Explaining Neural Networks via Partitioning Activation Sequences. CoRR abs/1811.02783 (2018) - 2017
- [j45]Konstantin Bauman, Alexander Tuzhilin, Ryan Zaczynski:
Using Social Sensors for Detecting Emergency Events: A Case of Power Outages in the Electrical Utility Industry. ACM Trans. Manag. Inf. Syst. 8(2-3): 7:1-7:20 (2017) - [c53]Konstantin Bauman, Bing Liu, Alexander Tuzhilin:
Aspect Based Recommendations: Recommending Items with the Most Valuable Aspects Based on User Reviews. KDD 2017: 717-725 - [c52]Toine Bogers, Marijn Koolen, Bamshad Mobasher, Alan Said, Alexander Tuzhilin:
Workshop on Recommendation in Complex Scenarios (ComplexRec 2017). ComplexRec@RecSys 2017: 1-2 - [c51]Toine Bogers, Marijn Koolen, Bamshad Mobasher, Alan Said, Alexander Tuzhilin:
Workshop on Recommendation in Complex Scenarios: (ComplexRec 2017). RecSys 2017: 380-381 - [e5]Paolo Cremonesi, Francesco Ricci, Shlomo Berkovsky, Alexander Tuzhilin:
Proceedings of the Eleventh ACM Conference on Recommender Systems, RecSys 2017, Como, Italy, August 27-31, 2017. ACM 2017, ISBN 978-1-4503-4652-8 [contents] - [e4]Toine Bogers, Marijn Koolen, Bamshad Mobasher, Alan Said, Alexander Tuzhilin:
Proceedings of the RecSys 2017 Workshop on Recommendation in Complex Scenarios co-located with 11th ACM Conference on Recommender Systems (RecSys 2017), Como, Italy, August 31, 2017. CEUR Workshop Proceedings 1892, CEUR-WS.org 2017 [contents] - 2016
- [j44]Dietmar Jannach, Paul Resnick, Alexander Tuzhilin, Markus Zanker:
Recommender systems - : beyond matrix completion. Commun. ACM 59(11): 94-102 (2016) - [j43]Umberto Panniello, Michele Gorgoglione, Alexander Tuzhilin:
Research Note - In CARSs We Trust: How Context-Aware Recommendations Affect Customers' Trust and Other Business Performance Measures of Recommender Systems. Inf. Syst. Res. 27(1): 182-196 (2016) - [c50]Konstantin Bauman, Bing Liu, Alexander Tuzhilin:
Recommending Items with Conditions Enhancing User Experiences Based on Sentiment Analysis of Reviews. CBRecSys@RecSys 2016: 19-22 - [i2]Julia Kiseleva, Alexander Tuzhilin, Jaap Kamps, Melanie J. I. Müller, Lucas Bernardi, Chad Davis, Ivan Kovacek, Mats Stafseng Einarsen, Djoerd Hiemstra:
Beyond Movie Recommendations: Solving the Continuous Cold Start Problem in E-commerceRecommendations. CoRR abs/1607.07904 (2016) - 2015
- [c49]Panagiotis Adamopoulos, Alexander Tuzhilin:
The Business Value of Recommendations: A Privacy-Preserving Econometric Analysis. ICIS 2015 - [c48]Panagiotis Adamopoulos, Alexander Tuzhilin, Peter Mountanos:
Measuring the Concentration Reinforcement Bias of Recommender Systems. RecSys Posters 2015 - [c47]Julia Kiseleva, Melanie J. I. Müller, Lucas Bernardi, Chad Davis, Ivan Kovacek, Mats Stafseng Einarsen, Jaap Kamps, Alexander Tuzhilin, Djoerd Hiemstra:
Where to Go on Your Next Trip?: Optimizing Travel Destinations Based on User Preferences. SIGIR 2015: 1097-1100 - [e3]Charu C. Aggarwal, Zhi-Hua Zhou, Alexander Tuzhilin, Hui Xiong, Xindong Wu:
2015 IEEE International Conference on Data Mining, ICDM 2015, Atlantic City, NJ, USA, November 14-17, 2015. IEEE Computer Society 2015, ISBN 978-1-4673-9504-5 [contents] - [r1]Gediminas Adomavicius, Alexander Tuzhilin:
Context-Aware Recommender Systems. Recommender Systems Handbook 2015: 191-226 - [i1]Julia Kiseleva, Melanie J. I. Müller, Lucas Bernardi, Chad Davis, Ivan Kovacek, Mats Stafseng Einarsen, Jaap Kamps, Alexander Tuzhilin, Djoerd Hiemstra:
Where to Go on Your Next Trip? Optimizing Travel Destinations Based on User Preferences. CoRR abs/1506.00904 (2015) - 2014
- [j42]Panagiotis Adamopoulos, Alexander Tuzhilin:
On Unexpectedness in Recommender Systems: Or How to Better Expect the Unexpected. ACM Trans. Intell. Syst. Technol. 5(4): 54:1-54:32 (2014) - [j41]Yong Ge, Hui Xiong, Alexander Tuzhilin, Qi Liu:
Cost-Aware Collaborative Filtering for Travel Tour Recommendations. ACM Trans. Inf. Syst. 32(1): 4:1-4:31 (2014) - [j40]Umberto Panniello, Alexander Tuzhilin, Michele Gorgoglione:
Comparing context-aware recommender systems in terms of accuracy and diversity. User Model. User Adapt. Interact. 24(1-2): 35-65 (2014) - [c46]Panagiotis Adamopoulos, Alexander Tuzhilin:
Estimating the Value of Multi-Dimensional Data Sets in Context-based Recommender Systems. RecSys Posters 2014 - [c45]Konstantin Bauman, Alexander Tuzhilin:
Discovering Contextual Information from User Reviews for Recommendation Purposes. CBRecSys@RecSys 2014: 2-9 - [c44]Panagiotis Adamopoulos, Alexander Tuzhilin:
On over-specialization and concentration bias of recommendations: probabilistic neighborhood selection in collaborative filtering systems. RecSys 2014: 153-160 - [c43]Konstantin Bauman, Alexander Tuzhilin:
Recommending Learning Materials to Students by Identifying their Knowledge Gaps. RecSys Posters 2014 - 2013
- [j39]Hui Xiong, Shashi Shekhar, Alexander Tuzhilin:
Introduction to special section on intelligent mobile knowledge discovery and management systems. ACM Trans. Intell. Syst. Technol. 5(1): 1:1-1:2 (2013) - [c42]Panagiotis Adamopoulos, Alexander Tuzhilin:
Recommendation opportunities: improving item prediction using weighted percentile methods in collaborative filtering systems. RecSys 2013: 351-354 - [c41]Daria Dzyabura, Alexander Tuzhilin:
Not by search alone: how recommendations complement search results. RecSys 2013: 371-374 - 2012
- [j38]Alexander Tuzhilin:
Customer relationship management and Web mining: the next frontier. Data Min. Knowl. Discov. 24(3): 584-612 (2012) - [c40]Gediminas Adomavicius, Linas Baltrunas, Ernesto William De Luca, Tim Hussein, Alexander Tuzhilin:
4th workshop on context-aware recommender systems (CARS 2012). RecSys 2012: 349-350 - 2011
- [j37]Gediminas Adomavicius, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin:
Context-Aware Recommender Systems. AI Mag. 32(3): 67-80 (2011) - [j36]Wenji Mao, Alexander Tuzhilin, Jonathan Gratch:
Social and Economic Computing. IEEE Intell. Syst. 26(6): 19-21 (2011) - [j35]Gediminas Adomavicius, Alexander Tuzhilin, Rong Zheng:
REQUEST: A Query Language for Customizing Recommendations. Inf. Syst. Res. 22(1): 99-117 (2011) - [j34]Alexander Tuzhilin:
Knowledge management revisited: Old Dogs, New tricks. ACM Trans. Manag. Inf. Syst. 2(3): 13:1-13:11 (2011) - [j33]Akhmed Umyarov, Alexander Tuzhilin:
Using external aggregate ratings for improving individual recommendations. ACM Trans. Web 5(1): 3:1-3:40 (2011) - [c39]Yong Ge, Qi Liu, Hui Xiong, Alexander Tuzhilin, Jian Chen:
Cost-aware travel tour recommendation. KDD 2011: 983-991 - [c38]Panagiotis Adamopoulos, Alexander Tuzhilin:
On Unexpectedness in Recommender Systems: Or How to Expect the Unexpected. DiveRS@RecSys 2011: 11-18 - [c37]Michele Gorgoglione, Umberto Panniello, Alexander Tuzhilin:
The effect of context-aware recommendations on customer purchasing behavior and trust. RecSys 2011: 85-92 - [c36]Yong Ge, Hui Xiong, Alexander Tuzhilin, Qi Liu:
Collaborative filtering with collective training. RecSys 2011: 281-284 - [c35]Gediminas Adomavicius, Linas Baltrunas, Tim Hussein, Francesco Ricci, Alexander Tuzhilin:
3rd workshop on context-aware recommender systems (CARS 2011). RecSys 2011: 379-380 - [p3]Gediminas Adomavicius, Alexander Tuzhilin:
Context-Aware Recommender Systems. Recommender Systems Handbook 2011: 217-253 - 2010
- [c34]Yong Ge, Hui Xiong, Alexander Tuzhilin, Keli Xiao, Marco Gruteser, Michael J. Pazzani:
An energy-efficient mobile recommender system. KDD 2010: 899-908 - [c33]Gediminas Adomavicius, Alexander Tuzhilin, Shlomo Berkovsky, Ernesto William De Luca, Alan Said:
Context-awareness in recommender systems: research workshop and movie recommendation challenge. RecSys 2010: 385-386
2000 – 2009
- 2009
- [j32]Tianyi Jiang, Alexander Tuzhilin:
Dynamic micro-targeting: fitness-based approach to predicting individual preferences. Knowl. Inf. Syst. 19(3): 337-360 (2009) - [j31]Tianyi Jiang, Alexander Tuzhilin:
Improving Personalization Solutions through Optimal Segmentation of Customer Bases. IEEE Trans. Knowl. Data Eng. 21(3): 305-320 (2009) - [j30]Bamshad Mobasher, Alexander Tuzhilin:
Preface to the special issue on data mining for personalization. User Model. User Adapt. Interact. 19(1-2): 1-3 (2009) - [c32]Akhmed Umyarov, Alexander Tuzhilin:
Improving rating estimation in recommender systems using aggregation- and variance-based hierarchical models. RecSys 2009: 37-44 - [c31]Umberto Panniello, Alexander Tuzhilin, Michele Gorgoglione, Cosimo Palmisano, Anto Pedone:
Experimental comparison of pre- vs. post-filtering approaches in context-aware recommender systems. RecSys 2009: 265-268 - [e2]Lawrence D. Bergman, Alexander Tuzhilin, Robin D. Burke, Alexander Felfernig, Lars Schmidt-Thieme:
Proceedings of the 2009 ACM Conference on Recommender Systems, RecSys 2009, New York, NY, USA, October 23-25, 2009. ACM 2009, ISBN 978-1-60558-435-5 [contents] - 2008
- [j29]Bing Liu, Alexander Tuzhilin:
Managing large collections of data mining models. Commun. ACM 51(2): 85-89 (2008) - [j28]Cosimo Palmisano, Alexander Tuzhilin, Michele Gorgoglione:
Using Context to Improve Predictive Modeling of Customers in Personalization Applications. IEEE Trans. Knowl. Data Eng. 20(11): 1535-1549 (2008) - [c30]Maria Francesca Faraone, Michele Gorgoglione, Sabrina Lombardi, Cosimo Palmisano, Umberto Panniello, Alexander Tuzhilin:
The Effect of Context on the Predictive Performance of Segmentation. Web Intelligence/IAT Workshops 2008: 63-66 - [c29]Akhmed Umyarov, Alexander Tuzhilin:
Improving Collaborative Filtering Recommendations Using External Data. ICDM 2008: 618-627 - [c28]Ravi Kumar, Alexander Tuzhilin, Christos Faloutsos, David D. Jensen, Gueorgi Kossinets, Jure Leskovec, Andrew Tomkins:
Social networks: looking ahead. KDD 2008: 1060 - [c27]Yoon-Joo Park, Alexander Tuzhilin:
The long tail of recommender systems and how to leverage it. RecSys 2008: 11-18 - [c26]Gediminas Adomavicius, Alexander Tuzhilin:
Context-aware recommender systems. RecSys 2008: 335-336 - 2007
- [j27]Gediminas Adomavicius, Alexander Tuzhilin:
Validation Sequence Optimization: A Theoretical Approach. INFORMS J. Comput. 19(2): 185-200 (2007) - [c25]Cosimo Palmisano, Alexander Tuzhilin, Michele Gorgoglione:
User Profiling with Hierarchical Context: An e-Retailer Case Study. CONTEXT 2007: 369-383 - [c24]Tianyi Jiang, Alexander Tuzhilin:
Dynamic Micro Targeting: Fitness-Based Approach to Predicting Individual Preferences. ICDM 2007: 173-182 - [c23]