Gediminas Adomavicius

Publication Activity (10 Years)

Years Active: 1997-2024
Publications (10 Years): 41

Top Topics

User Preferences

Combinatorial Auctions

Tensor Factorization

Recommender Systems

Top Venues

Inf. Syst. Res.

INFORMS J. Comput.

Publications

Xuan Bi, Mochen Yang, Gediminas Adomavicius
Consumer Acquisition for Recommender Systems: A Theoretical Framework and Empirical Evaluations. Inf. Syst. Res. 35 (1) (2024)
Scott Schanke, Gautam Ray, Gediminas Adomavicius, Mihir Wagle
Content and Style of Firm-Generated Posts on Social Media: A Study of User Engagement on Hedonic and Utilitarian Product Pages on Facebook. J. Assoc. Inf. Syst. 25 (2) (2024)
Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Alexander Tuzhilin, Moshe Unger
Workshop on Context-Aware Recommender Systems 2023. RecSys (2023)
Gediminas Adomavicius, Alok Gupta, Mochen Yang
Bidder Support in Multi-item Multi-unit Continuous Combinatorial Auctions: A Unifying Theoretical Framework. Inf. Syst. Res. 33 (4) (2022)
Xuan Bi, Gediminas Adomavicius, William Li, Annie Qu
Improving Sales Forecasting Accuracy: A Tensor Factorization Approach with Demand Awareness. INFORMS J. Comput. 34 (3) (2022)
Gediminas Adomavicius, Yaqiong Wang
Improving Reliability Estimation for Individual Numeric Predictions: A Machine Learning Approach. INFORMS J. Comput. 34 (1) (2022)
Gediminas Adomavicius, Jesse C. Bockstedt, Shawn P. Curley, Jingjing Zhang
Effects of Personalized Recommendations Versus Aggregate Ratings on Post-Consumption Preference Responses. MIS Q. 46 (1) (2022)
Gediminas Adomavicius, Jesse C. Bockstedt, Shawn P. Curley, Jingjing Zhang
Recommender Systems, Ground Truth, and Preference Pollution. AI Mag. 43 (2) (2022)
Gediminas Adomavicius, Mochen Yang
Integrating Behavioral, Economic, and Technical Insights to Understand and Address Algorithmic Bias: A Human-Centric Perspective. ACM Trans. Manag. Inf. Syst. 13 (3) (2022)
Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger
CARS: Workshop on Context-Aware Recommender Systems 2022. RecSys (2022)
Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger
Workshop on Context-Aware Recommender Systems (CARS) 2021. RecSys (2021)
Gediminas Adomavicius, Jesse C. Bockstedt, Shawn P. Curley, Jingjing Zhang
Effects of Personalized and Aggregate Top-N Recommendation Lists on User Preference Ratings. ACM Trans. Inf. Syst. 39 (2) (2021)
Gediminas Adomavicius, Dietmar Jannach, Stephan Leitner, Jingjing Zhang
Understanding Longitudinal Dynamics of Recommender Systems with Agent-Based Modeling and Simulation. CoRR (2021)
Mochen Yang, Yuqing Ren, Gediminas Adomavicius
Engagement by Design: An Empirical Study of the "Reactions" Feature on Facebook Business Pages. ACM Trans. Comput. Hum. Interact. 27 (6) (2020)
Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger
Workshop on Context-Aware Recommender Systems. RecSys (2020)
Jingjing Zhang, Gediminas Adomavicius, Alok Gupta, Wolfgang Ketter
Consumption and Performance: Understanding Longitudinal Dynamics of Recommender Systems via an Agent-Based Simulation Framework. Inf. Syst. Res. 31 (1) (2020)
Xuan Bi, Gediminas Adomavicius, William Li, Annie Qu
Improving Sales Forecasting Accuracy: A Tensor Factorization Approach with Demand Awareness. CoRR (2020)
Himan Abdollahpouri, Gediminas Adomavicius, Robin Burke, Ido Guy, Dietmar Jannach, Toshihiro Kamishima, Jan Krasnodebski, Luiz Augusto Pizzato
Multistakeholder recommendation: Survey and research directions. User Model. User Adapt. Interact. 30 (1) (2020)
Mochen Yang, Edward McFowland III, Gordon Burtch, Gediminas Adomavicius
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem. CoRR (2020)
Himan Abdollahpouri, Gediminas Adomavicius, Robin Burke, Ido Guy, Dietmar Jannach, Toshihiro Kamishima, Jan Krasnodebski, Luiz Augusto Pizzato
Beyond Personalization: Research Directions in Multistakeholder Recommendation. CoRR (2019)
Qian Zhao, Martijn C. Willemsen, Gediminas Adomavicius, F. Maxwell Harper, Joseph A. Konstan
From preference into decision making: modeling user interactions in recommender systems. RecSys (2019)
Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger
Workshop on context-aware recommender systems. RecSys (2019)
Mochen Yang, Gediminas Adomavicius, Alok Gupta
Efficient Computational Strategies for Dynamic Inventory Liquidation. Inf. Syst. Res. 30 (2) (2019)
Konstantina Valogianni, Wolfgang Ketter, John Collins, Gediminas Adomavicius
Heterogeneous Electric Vehicle Charging Coordination: A Variable Charging Speed Approach. HICSS (2019)
Gediminas Adomavicius, Alok Gupta, Mochen Yang
Designing Real-Time Feedback for Bidders in Homogeneous-Item Continuous Combinatorial Auctions. MIS Q. 43 (3) (2019)
Mochen Yang, Yuqing Ren, Gediminas Adomavicius
Understanding User-Generated Content and Customer Engagement on Facebook Business Pages. Inf. Syst. Res. 30 (3) (2019)
Gediminas Adomavicius, Jesse C. Bockstedt, Shawn P. Curley, Jingjing Zhang
Reeducing Recommender System Biases: An Investigation of Rating Display Designs. MIS Q. 43 (4) (2019)
Qian Zhao, Martijn C. Willemsen, Gediminas Adomavicius, F. Maxwell Harper, Joseph A. Konstan
Interpreting user inaction in recommender systems. RecSys (2018)
Qian Zhao, F. Maxwell Harper, Gediminas Adomavicius, Joseph A. Konstan
Explicit or implicit feedback? engagement or satisfaction?: a field experiment on machine-learning-based recommender systems. SAC (2018)
Mochen Yang, Gediminas Adomavicius, Gordon Burtch, Yuqing Ren
Mind the Gap: Accounting for Measurement Error and Misclassification in Variables Generated via Data Mining. Inf. Syst. Res. 29 (1) (2018)
Gediminas Adomavicius, Jesse C. Bockstedt, Shawn P. Curley, Jingjing Zhang
Effects of Online Recommendations on Consumers' Willingness to Pay. Inf. Syst. Res. 29 (1) (2018)
Qian Zhao, Gediminas Adomavicius, F. Maxwell Harper, Martijn C. Willemsen, Joseph A. Konstan
Toward Better Interactions in Recommender Systems: Cycling and Serpentining Approaches for Top-N Item Lists. CSCW (2017)
Robin Burke, Gediminas Adomavicius, Ido Guy, Jan Krasnodebski, Luiz Augusto Pizzato, Yi Zhang, Himan Abdollahpouri
VAMS 2017: Workshop on Value-Aware and Multistakeholder Recommendation. RecSys (2017)
Bryan D. Martin, Vittorio Addona, Julian Wolfson, Gediminas Adomavicius, Yingling Fan
Methods for Real-Time Prediction of the Mode of Travel Using Smartphone-Based GPS and Accelerometer Data. Sensors 17 (9) (2017)
Ali Mahdavi Adeli, Gediminas Adomavicius, Alok Gupta
Toward Understanding the Dynamics of Bidder Behavior in Continuous Combinatorial Auctions: Agent-Based Simulation Approach. HICSS (2017)
Martin Bichler, Zhen Hao, Gediminas Adomavicius
Coalition-Based Pricing in Ascending Combinatorial Auctions. Inf. Syst. Res. 28 (1) (2017)
Dietmar Jannach, Gediminas Adomavicius
Price and Profit Awareness in Recommender Systems. CoRR (2017)
Gediminas Adomavicius, Jesse C. Bockstedt, Shawn P. Curley, Jingjing Zhang
Understanding Effects of Personalized vs. Aggregate Ratings on User Preferences. IntRS@RecSys (2016)
David M. Vock, Julian Wolfson, Sunayan Bandyopadhyay, Gediminas Adomavicius, Paul E. Johnson, Gabriela Vazquez-Benitez, Patrick J. O'Connor
Adapting machine learning techniques to censored time-to-event health record data: A general-purpose approach using inverse probability of censoring weighting. J. Biomed. Informatics 61 (2016)
Dietmar Jannach, Gediminas Adomavicius
Recommendations with a Purpose. RecSys (2016)
Gediminas Adomavicius, Jingjing Zhang
Classification, Ranking, and Top-K Stability of Recommendation Algorithms. INFORMS J. Comput. 28 (1) (2016)
Gediminas Adomavicius, Jesse C. Bockstedt, Shawn P. Curley
Bundling Effects on Variety Seeking for Digital Information Goods. J. Manag. Inf. Syst. 31 (4) (2015)
Sunayan Bandyopadhyay, Julian Wolfson, David M. Vock, Gabriela Vazquez-Benitez, Gediminas Adomavicius, Mohamed Elidrisi, Paul E. Johnson, Patrick J. O'Connor
Data mining for censored time-to-event data: a Bayesian network model for predicting cardiovascular risk from electronic health record data. Data Min. Knowl. Discov. 29 (4) (2015)
Gediminas Adomavicius, Jingjing Zhang
Improving Stability of Recommender Systems: A Meta-Algorithmic Approach. IEEE Trans. Knowl. Data Eng. 27 (6) (2015)
Martin Bichler, Zhen Hao, Gediminas Adomavicius
Coordination and Pricing in Multi-Object Auctions. ICIS (2015)
Georg Meyer, Gediminas Adomavicius, Paul E. Johnson, Mohamed Elidrisi, William A. Rush, JoAnn M. Sperl-Hillen, Patrick J. O'Connor
A Machine Learning Approach to Improving Dynamic Decision Making. Inf. Syst. Res. 25 (2) (2014)
Gediminas Adomavicius, YoungOk Kwon
Optimization-Based Approaches for Maximizing Aggregate Recommendation Diversity. INFORMS J. Comput. 26 (2) (2014)
Gediminas Adomavicius, Dietmar Jannach
Preface to the special issue on context-aware recommender systems. User Model. User Adapt. Interact. 24 (1-2) (2014)
Gediminas Adomavicius, Shawn P. Curley, Alok Gupta, Pallab Sanyal
Impact of Information Feedback in Continuous Combinatorial Auctions: An Experimental Study of Economic Performance. MIS Q. 37 (1) (2013)
Gediminas Adomavicius, Jesse C. Bockstedt, Shawn P. Curley, Jingjing Zhang
Do Recommender Systems Manipulate Consumer Preferences? A Study of Anchoring Effects. Inf. Syst. Res. 24 (4) (2013)
Joseph A. Konstan, Gediminas Adomavicius
Toward identification and adoption of best practices in algorithmic recommender systems research. RepSys@RecSys (2013)
Gediminas Adomavicius, Alok Gupta, Pallab Sanyal
Effect of Information Feedback on the Outcomes and Dynamics of Multisourcing Multiattribute Procurement Auctions. J. Manag. Inf. Syst. 28 (4) (2012)
Gediminas Adomavicius, Shawn P. Curley, Alok Gupta, Pallab Sanyal
Effect of Information Feedback on Bidder Behavior in Continuous Combinatorial Auctions. Manag. Sci. 58 (4) (2012)
Gediminas Adomavicius, YoungOk Kwon
Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques. IEEE Trans. Knowl. Data Eng. 24 (5) (2012)
Gediminas Adomavicius, Jesse C. Bockstedt, Alok Gupta
Modeling Supply-Side Dynamics of IT Components, Products, and Infrastructure: An Empirical Analysis Using Vector Autoregression. Inf. Syst. Res. 23 (2) (2012)
Gediminas Adomavicius, Jingjing Zhang
Stability of Recommendation Algorithms. ACM Trans. Inf. Syst. 30 (4) (2012)
Gediminas Adomavicius, Jingjing Zhang
Iterative Smoothing Technique for Improving the Stability of Recommender Systems. RUE@RecSys (2012)
Gediminas Adomavicius, Jesse C. Bockstedt, Shawn P. Curley, Jingjing Zhang
Effects of Online Recommendations on Consumers' Willingness to Pay. Decisions@RecSys (2012)
Gediminas Adomavicius, Jingjing Zhang
Impact of data characteristics on recommender systems performance. ACM Trans. Manag. Inf. Syst. 3 (1) (2012)
Gediminas Adomavicius, Linas Baltrunas, Ernesto William De Luca, Tim Hussein, Alexander Tuzhilin
4th workshop on context-aware recommender systems (CARS 2012). RecSys (2012)
Gediminas Adomavicius, Alexander Tuzhilin, Rong Zheng
REQUEST: A Query Language for Customizing Recommendations. Inf. Syst. Res. 22 (1) (2011)
Gediminas Adomavicius, Linas Baltrunas, Tim Hussein, Francesco Ricci, Alexander Tuzhilin
3rd workshop on context-aware recommender systems (CARS 2011). RecSys (2011)
Gediminas Adomavicius, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin
Context-Aware Recommender Systems. AI Mag. 32 (3) (2011)
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)
Gediminas Adomavicius, Jingjing Zhang
On the stability of recommendation algorithms. RecSys (2010)
Gediminas Adomavicius, Alok Gupta, Dmitry Zhdanov
Designing Intelligent Software Agents for Auctions with Limited Information Feedback. Inf. Syst. Res. 20 (4) (2009)
Gediminas Adomavicius, Francesco Ricci
RecSys'09 workshop 3: workshop on context-aware recommender systems (CARS-2009). RecSys (2009)
Gediminas Adomavicius, Alok Gupta, Pallab Sanyal
Design and Evaluation of Feedback Schemes for Multiattribute Procurement Auctions. ICIS (2008)
Gediminas Adomavicius, Jesse C. Bockstedt
C-TREND: Temporal Cluster Graphs for Identifying and Visualizing Trends in Multiattribute Transactional Data. IEEE Trans. Knowl. Data Eng. 20 (6) (2008)
Gediminas Adomavicius, Jesse C. Bockstedt, Alok Gupta, Robert J. Kauffman
Understanding evolution in technology ecosystems. Commun. ACM 51 (10) (2008)
Gediminas Adomavicius, Jesse C. Bockstedt, Alok Gupta, Robert J. Kauffman
Making Sense of Technology Trends in the Information Technology Landscape: A Design Science Approach. MIS Q. 32 (4) (2008)
Gediminas Adomavicius, Alexander Tuzhilin
Context-aware recommender systems. RecSys (2008)
Gediminas Adomavicius, Jesse C. Bockstedt, Alok Gupta, Robert J. Kauffman
Technology roles and paths of influence in an ecosystem model of technology evolution. Inf. Technol. Manag. 8 (2) (2007)
Gediminas Adomavicius, Pallab Sanyal, Alok Gupta, Shawn P. Curley
Design and Effects of Information Feedback in Continuous Combinatorial Auctions. ICIS (2007)
Gediminas Adomavicius, YoungOk Kwon
New Recommendation Techniques for Multicriteria Rating Systems. IEEE Intell. Syst. 22 (3) (2007)
Gediminas Adomavicius, Alexander Tuzhilin
Validation Sequence Optimization: A Theoretical Approach. INFORMS J. Comput. 19 (2) (2007)
Gediminas Adomavicius, Alexander Tuzhilin
Personalization technologies: A process-oriented perspective. Wirtschaftsinf. 48 (6) (2006)
Gediminas Adomavicius, Jesse C. Bockstedt, Alok Gupta, Robert J. Kauffman
Understanding Patterns of Technology Evolution: An Ecosystem Perspective. HICSS (2006)
Gediminas Adomavicius, Alexander Tuzhilin
Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions. IEEE Trans. Knowl. Data Eng. 17 (6) (2005)
Gediminas Adomavicius, Alexander Tuzhilin
Personalization technologies: a process-oriented perspective. Commun. ACM 48 (10) (2005)
Gediminas Adomavicius, Ramesh Sankaranarayanan, Shahana Sen, Alexander Tuzhilin
Incorporating contextual information in recommender systems using a multidimensional approach. ACM Trans. Inf. Syst. 23 (1) (2005)
Gediminas Adomavicius, Alok Gupta
Toward Comprehensive Real-Time Bidder Support in Iterative Combinatorial Auctions. Inf. Syst. Res. 16 (2) (2005)
Alexander Tuzhilin, Gediminas Adomavicius
Handling very large numbers of association rules in the analysis of microarray data. KDD (2002)
Gediminas Adomavicius, Alexander Tuzhilin
An Architecture of e-Butler: A Consumer-Centric Online Personalization System. Int. J. Comput. Intell. Appl. 2 (3) (2002)
Gediminas Adomavicius, Alexander Tuzhilin
Using Data Mining Methods to Build Customer Profiles. Computer 34 (2) (2001)
Gediminas Adomavicius, Alexander Tuzhilin
Multidimensional Recommender Systems: A Data Warehousing Approach. WELCOM (2001)
Gediminas Adomavicius, Alexander Tuzhilin
Expert-Driven Validation of Rule-Based User Models in Personalization Applications. Data Min. Knowl. Discov. 5 (1/2) (2001)
Gediminas Adomavicius, Alexander Tuzhilin
User Profiling in Personalization Applications Through Rule Discovery and Validation. KDD (1999)
Gediminas Adomavicius, Alexander Tuzhilin
Discovery of Actionable Patterns in Databases: The Action Hierarchy Approach. KDD (1997)