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- affiliation: DePaul University, Chicago, IL, USA
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2020 – today
- 2024
[c148]Masoud Mansoury
, Bamshad Mobasher, Herke van Hoof:
Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits. CIKM 2024: 1638-1648- [c147]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Alexander Tuzhilin, Moshe Unger:
Workshop on Context-Aware Recommender Systems (CARS) 2024. RecSys 2024: 1219-1221 - [c146]Kun Lin, Masoud Mansoury, Farzad Eskandanian, Milad Sabouri, Bamshad Mobasher:
Beyond Static Calibration: The Impact of User Preference Dynamics on Calibrated Recommendation. UMAP (Adjunct Publication) 2024 - [i33]Kun Lin, Masoud Mansoury, Farzad Eskandanian, Milad Sabouri, Bamshad Mobasher:
Beyond Static Calibration: The Impact of User Preference Dynamics on Calibrated Recommendation. CoRR abs/2405.10232 (2024) - [i32]Masoud Mansoury, Bamshad Mobasher, Herke van Hoof:
Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits. CoRR abs/2408.04332 (2024) - 2023
- [c145]Payam Pourashraf, Bamshad Mobasher:
Modeling Users' Localized Preferences for More Effective News Recommendation. HCI (41) 2023: 366-382 - [c144]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Alexander Tuzhilin, Moshe Unger:
Workshop on Context-Aware Recommender Systems 2023. RecSys 2023: 1234-1236 - [c143]Bamshad Mobasher, Styliani Kleanthous, Jahna Otterbacher, Robin Burke, Avital Shulner-Tal:
6th Workshop on Fairness in User Modeling, Adaptation, and Personalization (FairUMAP 2023). UMAP (Adjunct Publication) 2023: 239-240 - [i31]Masoud Mansoury, Bamshad Mobasher:
Fairness of Exposure in Dynamic Recommendation. CoRR abs/2309.02322 (2023) - 2022
- [j40]Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke:
A Graph-Based Approach for Mitigating Multi-Sided Exposure Bias in Recommender Systems. ACM Trans. Inf. Syst. 40(2): 32:1-32:31 (2022) - [c142]Shoujin Wang, Ninghao Liu, Xiuzhen Zhang, Yan Wang, Francesco Ricci, Bamshad Mobasher:
Data Science and Artificial Intelligence for Responsible Recommendations. KDD 2022: 4904-4905 - [c141]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger:
CARS: Workshop on Context-Aware Recommender Systems 2022. RecSys 2022: 691-693 - [c140]Payam Pourashraf, Bamshad Mobasher:
Using Recommender Systems to Help Revitalize Local News. UMAP (Adjunct Publication) 2022: 80-84 - [c139]Mohammed Muheeb Ghori, Arman Dehpanah, Jonathan Gemmell, Hamed Qahri-Saremi, Bamshad Mobasher:
Does the User Have A Theory of the Recommender? A Grounded Theory Study. UMAP (Adjunct Publication) 2022: 167-174 - [c138]Styliani Kleanthous, Bamshad Mobasher, Tsvika Kuflik, Bettina Berendt, Robin Burke, Jahna Otterbacher, Nasim Sonboli, Avital Shulner-Tal:
5th Workshop on Fairness in User Modeling, Adaptation, and Personalization (FairUMAP 2022). UMAP (Adjunct Publication) 2022: 209-210 - [c137]Payam Pourashraf, Bamshad Mobasher:
Using user's local context to support local news. UMAP (Adjunct Publication) 2022: 359-365 - [i30]Payam Pourashraf, Bamshad Mobasher:
Using user's local context to support local news. CoRR abs/2205.12408 (2022) - [i29]Arman Dehpanah, Muheeb Faizan Ghori, Jonathan Gemmell, Bamshad Mobasher:
Behavioral Player Rating in Competitive Online Shooter Games. CoRR abs/2207.00528 (2022) - [i28]Masoud Mansoury, Bamshad Mobasher, Herke van Hoof:
Exposure-Aware Recommendation using Contextual Bandits. CoRR abs/2209.01665 (2022) - 2021
- [j39]Vito Walter Anelli, Pierpaolo Basile, Toine Bogers, Tommaso Di Noia, Francesco Maria Donini, Bamshad Mobasher, Cataldo Musto, Fedelucio Narducci, Casper Petersen, Maria Soledad Pera, Markus Zanker:
Report on the 3rd workshop of knowledge-aware and conversational recommender systems (KARS/ComplexRec) at RecSys 2021. SIGIR Forum 55(2): 17:1-17:9 (2021) - [j38]Masoud Mansoury, Robin Burke, Bamshad Mobasher:
Flatter Is Better: Percentile Transformations for Recommender Systems. ACM Trans. Intell. Syst. Technol. 12(2): 19:1-19:16 (2021) - [c136]Arman Dehpanah, Muheeb Faizan Ghori, Jonathan Gemmell, Bamshad Mobasher:
Evaluating Team Skill Aggregation in Online Competitive Games. CoG 2021: 1-8 - [c135]Arman Dehpanah, Muheeb Faizan Ghori, Jonathan Gemmell, Bamshad Mobasher:
Player Modeling using Behavioral Signals in Competitive Online Games. CSCI 2021: 569-574 - [c134]Muheeb Faizan Ghori, Arman Dehpanah, Jonathan Gemmell, Hamed Qahri-Saremi, Bamshad Mobasher:
How does the User's Knowledge of the Recommender Influence their Behavior? IntRS@RecSys 2021: 38-54 - [c133]Himan Abdollahpouri, Toine Bogers, Bamshad Mobasher, Casper Petersen, Maria Soledad Pera:
ComplexRec 2021: Fifth Workshop on Recommendation in Complex Environments. RecSys 2021: 775-777 - [c132]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger:
Workshop on Context-Aware Recommender Systems (CARS) 2021. RecSys 2021: 813-814 - [c131]Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher, Edward C. Malthouse:
User-centered Evaluation of Popularity Bias in Recommender Systems. UMAP 2021: 119-129 - [c130]Bamshad Mobasher, Styliani Kleanthous, Bettina Berendt, Jahna Otterbacher, Tsvi Kuflik, Avital Shulner-Tal:
FairUMAP 2021: The 4th Workshop on Fairness in User Modeling, Adaptation and Personalization. UMAP (Adjunct Publication) 2021: 399-400 - [c129]Himan Abdollahpouri, Edward C. Malthouse, Joseph A. Konstan, Bamshad Mobasher, Jeremy Gilbert:
Toward the Next Generation of News Recommender Systems. WWW (Companion Volume) 2021: 402-406 - [e19]Vito Walter Anelli, Pierpaolo Basile, Tommaso Di Noia, Francesco Maria Donini, Cataldo Musto, Fedelucio Narducci, Markus Zanker, Himan Abdollahpouri, Toine Bogers, Bamshad Mobasher, Casper Petersen, Maria Soledad Pera:
Joint Workshop Proceedings of the 3rd Edition of Knowledge-aware and Conversational Recommender Systems (KaRS) and the 5th Edition of Recommendation in Complex Environments (ComplexRec) co-located with 15th ACM Conference on Recommender Systems (RecSys 2021), Virtual Event, Amsterdam, The Netherlands, September 25, 2021. CEUR Workshop Proceedings 2960, CEUR-WS.org 2021 [contents] - [i27]Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher, Edward C. Malthouse:
User-centered Evaluation of Popularity Bias in Recommender Systems. CoRR abs/2103.06364 (2021) - [i26]Himan Abdollahpouri, Edward C. Malthouse, Joseph A. Konstan, Bamshad Mobasher, Jeremy Gilbert:
Toward the Next Generation of News Recommender Systems. CoRR abs/2103.06909 (2021) - [i25]Arman Dehpanah, Muheeb Faizan Ghori, Jonathan Gemmell, Bamshad Mobasher:
The Evaluation of Rating Systems in Team-based Battle Royale Games. CoRR abs/2105.14069 (2021) - [i24]Arman Dehpanah, Muheeb Faizan Ghori, Jonathan Gemmell, Bamshad Mobasher:
Evaluating Team Skill Aggregation in Online Competitive Games. CoRR abs/2106.11397 (2021) - [i23]Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke:
A Graph-based Approach for Mitigating Multi-sided Exposure Bias in Recommender Systems. CoRR abs/2107.03415 (2021) - [i22]Masoud Mansoury, Himan Abdollahpouri, Bamshad Mobasher, Mykola Pechenizkiy, Robin Burke, Milad Sabouri:
Unbiased Cascade Bandits: Mitigating Exposure Bias in Online Learning to Rank Recommendation. CoRR abs/2108.03440 (2021) - [i21]Muheeb Faizan Ghori, Arman Dehpanah, Jonathan Gemmell, Hamed Qahri-Saremi, Bamshad Mobasher:
How does the User's Knowledge of the Recommender Influence their Behavior? CoRR abs/2109.00982 (2021) - [i20]Arman Dehpanah, Muheeb Faizan Ghori, Jonathan Gemmell, Bamshad Mobasher:
Player Modeling using Behavioral Signals in Competitive Online Games. CoRR abs/2112.04379 (2021) - 2020
- [j37]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) - [j36]Dietmar Jannach, Bamshad Mobasher, Shlomo Berkovsky:
Research directions in session-based and sequential recommendation. User Model. User Adapt. Interact. 30(4): 609-616 (2020) - [c128]Cynthia Putnam, Bamshad Mobasher:
Children with Autism and Technology Use: A Case Study of the Diary Method. CHI Extended Abstracts 2020: 1-8 - [c127]Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke:
Feedback Loop and Bias Amplification in Recommender Systems. CIKM 2020: 2145-2148 - [c126]Masoud Mansoury, Himan Abdollahpouri, Jessie Smith, Arman Dehpanah, Mykola Pechenizkiy, Bamshad Mobasher:
Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems. FLAIRS 2020: 193-196 - [c125]Kun Lin, Nasim Sonboli, Bamshad Mobasher, Robin Burke:
Calibration in Collaborative Filtering Recommender Systems: a User-Centered Analysis. HT 2020: 197-206 - [c124]Toine Bogers, Marijn Koolen, Casper Petersen, Bamshad Mobasher, Alexander Tuzhilin:
ComplexRec 2020: Workshop on Recommendation in Complex Environments. RecSys 2020: 609-610 - [c123]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger:
Workshop on Context-Aware Recommender Systems. RecSys 2020: 635-637 - [c122]Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher:
The Connection Between Popularity Bias, Calibration, and Fairness in Recommendation. RecSys 2020: 726-731 - [c121]Farzad Eskandanian, Bamshad Mobasher:
Using Stable Matching to Optimize the Balance between Accuracy and Diversity in Recommendation. UMAP 2020: 71-79 - [c120]Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke:
FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems. UMAP 2020: 154-162 - [c119]Nasim Sonboli, Farzad Eskandanian, Robin Burke, Weiwen Liu, Bamshad Mobasher:
Opportunistic Multi-aspect Fairness through Personalized Re-ranking. UMAP 2020: 239-247 - [c118]Bamshad Mobasher, Styliani Kleanthous, Bettina Berendt, Michael D. Ekstrand, Jahna Otterbacher, Avital Shulner-Tal:
UMAP 2020 Fairness in User Modeling, Adaptation and Personalization (FairUMAP 2020) Chairs' Welcome. UMAP (Adjunct Publication) 2020: 241-243 - [c117]Bamshad Mobasher, Styliani Kleanthous, Michael D. Ekstrand, Bettina Berendt, Jahna Otterbacher, Avital Shulner-Tal:
FairUMAP 2020: The 3rd Workshop on Fairness in User Modeling, Adaptation and Personalization. UMAP 2020: 404-405 - [c116]Diego Sánchez-Moreno, María N. Moreno García, Nasim Sonboli, Bamshad Mobasher, Robin Burke:
Using Social Tag Embedding in a Collaborative Filtering Approach for Recommender Systems. WI/IAT 2020: 502-507 - [e18]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] - [i19]Masoud Mansoury, Himan Abdollahpouri, Jessie Smith, Arman Dehpanah, Mykola Pechenizkiy, Bamshad Mobasher:
Investigating Potential Factors Associated with Gender Discrimination in Collaborative Recommender Systems. CoRR abs/2002.07786 (2020) - [i18]Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke:
FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems. CoRR abs/2005.01148 (2020) - [i17]Nasim Sonboli, Farzad Eskandanian, Robin Burke, Weiwen Liu, Bamshad Mobasher:
Opportunistic Multi-aspect Fairness through Personalized Re-ranking. CoRR abs/2005.12974 (2020) - [i16]Farzad Eskandanian, Bamshad Mobasher:
Using Stable Matching to Optimize the Balance between Accuracy and Diversity in Recommendation. CoRR abs/2006.03715 (2020) - [i15]Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher:
Addressing the Multistakeholder Impact of Popularity Bias in Recommendation Through Calibration. CoRR abs/2007.12230 (2020) - [i14]Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke:
Feedback Loop and Bias Amplification in Recommender Systems. CoRR abs/2007.13019 (2020) - [i13]Arman Dehpanah, Muheeb Faizan Ghori, Jonathan Gemmell, Bamshad Mobasher:
The Evaluation of Rating Systems in Online Free-for-All Games. CoRR abs/2008.06787 (2020) - [i12]Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher:
The Connection Between Popularity Bias, Calibration, and Fairness in Recommendation. CoRR abs/2008.09273 (2020)
2010 – 2019
- 2019
- [j35]Bamshad Mobasher, Lucia Dettori, Daniela Raicu, Raffaella Settimi, Nasim Sonboli, Monica Stettler:
Data Science Summer Academy for Chicago Public School Students. SIGKDD Explor. 21(1): 49-52 (2019) - [c115]Himan Abdollahpouri, Robin Burke, Bamshad Mobasher:
Managing Popularity Bias in Recommender Systems with Personalized Re-Ranking. FLAIRS 2019: 413-418 - [c114]Farzad Eskandanian, Bamshad Mobasher:
Modeling the Dynamics of User Preferences for Sequence-Aware Recommendation Using Hidden Markov Models. FLAIRS 2019: 425-430 - [c113]Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher:
The Unfairness of Popularity Bias in Recommendation. RMSE@RecSys 2019 - [c112]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 - [c111]Muheeb Faizan Ghori, Arman Dehpanah, Jonathan Gemmell, Hamed Qahri-Saremi, Bamshad Mobasher:
Does the User Have A Theory of the Recommender? A Pilot Study. IntRS@RecSys 2019: 77-85 - [c110]Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger:
Workshop on context-aware recommender systems. RecSys 2019: 548-549 - [c109]Marijn Koolen, Toine Bogers, Bamshad Mobasher, Alexander Tuzhilin:
Third workshop on recommendation in complex scenarios (ComplexRec 2019). RecSys 2019: 550-551 - [c108]Kun Lin, Nasim Sonboli, Bamshad Mobasher, Robin Burke:
Crank up the Volume: Preference Bias Amplification in Collaborative Recommendation. RMSE@RecSys 2019 - [c107]Masoud Mansoury, Bamshad Mobasher, Robin Burke, Mykola Pechenizkiy:
Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison. RMSE@RecSys 2019 - [c106]Geert-Jan Houben, Bamshad Mobasher:
UMAP 2019 Theory, Reflection, and Opinion Track: Chairs' Welcome and Overview. UMAP (Adjunct Publication) 2019: 1 - [c105]Farzad Eskandanian, Nasim Sonboli, Bamshad Mobasher:
Power of the Few: Analyzing the Impact of Influential Users in Collaborative Recommender Systems. UMAP 2019: 225-233 - [c104]Bettina Berendt, Veronika Bogina, Robin Burke, Michael D. Ekstrand, Alan Hartman, Styliani Kleanthous, Tsvi Kuflik, Bamshad Mobasher, Jahna Otterbacher:
FairUMAP 2019 Chairs' Welcome Overview. UMAP (Adjunct Publication) 2019: 279-281 - [e17]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] - [i11]Himan Abdollahpouri, Robin Burke, Bamshad Mobasher:
Managing Popularity Bias in Recommender Systems with Personalized Re-ranking. CoRR abs/1901.07555 (2019) - [i10]Farzad Eskandanian, Bamshad Mobasher:
Modeling the Dynamics of User Preferences for Sequence-Aware Recommendation Using Hidden Markov Models. CoRR abs/1905.06863 (2019) - [i9]Farzad Eskandanian, Nasim Sonboli, Bamshad Mobasher:
Power of the Few: Analyzing the Impact of Influential Users in Collaborative Recommender Systems. CoRR abs/1905.08031 (2019) - [i8]Masoud Mansoury, Robin Burke, Bamshad Mobasher:
Flatter is better: Percentile Transformations for Recommender Systems. CoRR abs/1907.07766 (2019) - [i7]Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher:
The Unfairness of Popularity Bias in Recommendation. CoRR abs/1907.13286 (2019) - [i6]Masoud Mansoury, Bamshad Mobasher, Robin Burke, Mykola Pechenizkiy:
Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and Comparison. CoRR abs/1908.00831 (2019) - [i5]Kun Lin, Nasim Sonboli, Bamshad Mobasher, Robin Burke:
Crank up the volume: preference bias amplification in collaborative recommendation. CoRR abs/1909.06362 (2019) - [i4]Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher:
The Impact of Popularity Bias on Fairness and Calibration in Recommendation. CoRR abs/1910.05755 (2019) - 2018
- [c103]Diego Sánchez-Moreno, María N. Moreno García, Nasim Sonboli, Bamshad Mobasher, Robin Burke:
Inferring User Expertise from Social Tagging in Music Recommender Systems for Streaming Services. HAIS 2018: 39-49 - [c102]Toine Bogers, Marijn Koolen, Bamshad Mobasher, Alan Said, Casper Petersen:
2nd workshop on recommendation in complex scenarios (complexrec 2018). RecSys 2018: 510-511 - [c101]Bamshad Mobasher, Robin Burke, Michael D. Ekstrand, Bettina Berendt:
UMAP 2018 Fairness in User Modeling, Adaptation and Personalization (FairUMAP 2018) Chairs' Welcome & Organization: Preface. UMAP (Adjunct Publication) 2018: 3-5 - [p3]Yong Zheng, Bamshad Mobasher:
Context-Aware Recommendations. Collaborative Recommendations 2018: 173-202 - [i3]Himan Abdollahpouri, Robin Burke, Bamshad Mobasher:
Value-Aware Item Weighting for Long-Tail Recommendation. CoRR abs/1802.05382 (2018) - [i2]Farzad Eskandanian, Bamshad Mobasher:
Detecting Changes in User Preferences using Hidden Markov Models for Sequential Recommendation Tasks. CoRR abs/1810.00272 (2018) - 2017
- [j34]Fatemeh Vahedian, Robin Burke, Bamshad Mobasher:
Multirelational Recommendation in Heterogeneous Networks. ACM Trans. Web 11(3): 15:1-15:34 (2017) - [c100]Laura Christiansen, Bamshad Mobasher, Robin Burke:
Using Uncertain Graphs to Automatically Generate Event Flows from News Stories. HT (Extended Proceedings) 2017 - [c99]Toine Bogers, Marijn Koolen, Bamshad Mobasher, Alan Said, Alexander Tuzhilin:
Workshop on Recommendation in Complex Scenarios (ComplexRec 2017). ComplexRec@RecSys 2017: 1-2 - [c98]Himan Abdollahpouri, Robin Burke, Bamshad Mobasher:
Controlling Popularity Bias in Learning-to-Rank Recommendation. RecSys 2017: 42-46 - [c97]Toine Bogers, Marijn Koolen, Bamshad Mobasher, Alan Said, Alexander Tuzhilin:
Workshop on Recommendation in Complex Scenarios: (ComplexRec 2017). RecSys 2017: 380-381 - [c96]Fatemeh Vahedian, Robin D. Burke, Bamshad Mobasher:
Weighted Random Walk Sampling for Multi-Relational Recommendation. UMAP 2017: 230-237 - [c95]Farzad Eskandanian, Bamshad Mobasher, Robin Burke:
A Clustering Approach for Personalizing Diversity in Collaborative Recommender Systems. UMAP 2017: 280-284 - [c94]Himan Abdollahpouri, Robin Burke, Bamshad Mobasher:
Recommender Systems as Multistakeholder Environments. UMAP 2017: 347-348 - [c93]Cataldo Musto, Amon Rapp, Veronika Bogina, Federica Cena, Frank Hopfgartner, Judy Kay, David Konopnicki, Tsvi Kuflik, Bamshad Mobasher, Giovanni Semeraro:
UMAP 2017 THUM Workshop Chairs' Welcome & Organization. UMAP (Adjunct Publication) 2017: 368-369 - [p2]Yong Zheng, Bamshad Mobasher, Robin Burke:
Emotions in Context-Aware Recommender Systems. Emotions and Personality in Personalized Services 2017: 311-326 - [e16]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] - [i1]Fatemeh Vahedian, Robin D. Burke, Bamshad Mobasher:
Weighted Random Walk Sampling for Multi-Relational Recommendation. CoRR abs/1703.00034 (2017) - 2016
- [c92]Fatemeh Vahedian, Robin D. Burke, Bamshad Mobasher:
Meta-Path Selection for Extended Multi-Relational Matrix Factorization. FLAIRS 2016: 566-571 - [c91]Farzad Eskandanian, Bamshad Mobasher, Robin D. Burke:
User Segmentation for Controlling Recommendation Diversity. RecSys Posters 2016 - [c90]Fatemeh Vahedian, Robin D. Burke, Bamshad Mobasher:
Weighted Random Walks for Meta-Path Expansion in Heterogeneous Networks. RecSys Posters 2016 - [c89]Robin D. Burke, Himan Abdollahpouri, Bamshad Mobasher, Trinadh Gupta:
Towards Multi-Stakeholder Utility Evaluation of Recommender Systems. UMAP (Extended Proceedings) 2016 - [c88]Yong Zheng, Bamshad Mobasher, Robin Burke:
User-Oriented Context Suggestion. UMAP 2016: 249-258 - 2015
- [c87]Yong Zheng, Bamshad Mobasher, Robin D. Burke:
CARSKit: A Java-Based Context-Aware Recommendation Engine. ICDM Workshops 2015: 1668-1671 - [c86]Negar Hariri, Bamshad Mobasher, Robin Burke:
Adapting to User Preference Changes in Interactive Recommendation. IJCAI 2015: 4268-4274 - [c85]Yong Zheng, Bamshad Mobasher, Robin D. Burke:
Incorporating Context Correlation into Context-aware Matrix Factorization. CPCR+ITWP@IJCAI 2015 - [c84]Mehdi Hosseinzadeh Aghdam, Negar Hariri, Bamshad Mobasher, Robin D. Burke:
Adapting Recommendations to Contextual Changes Using Hierarchical Hidden Markov Models. RecSys 2015: 241-244 - [c83]Fatemeh Vahedian, Robin D. Burke, Bamshad Mobasher:
Network-Based Extension of Multi-Relational Factorization Models. RecSys Posters 2015 - [c82]Chuan Duan, Horatiu Dumitru, Jane Cleland-Huang, Bamshad Mobasher:
User-Constrained Clustering in Online Requirements Forums. REFSQ 2015: 284-299 - [c81]Yong Zheng, Bamshad Mobasher, Robin D. Burke:
Integrating Context Similarity with Sparse Linear Recommendation Model. UMAP 2015: 370-376 - [c80]Yong Zheng, Bamshad Mobasher, Robin D. Burke:
Similarity-Based Context-Aware Recommendation. WISE (1) 2015: 431-447 - [e15]Dietmar Jannach, Jérôme Mengin, Bamshad Mobasher, Andrea Passerini, Paolo Viappiani:
Proceedings of the IJCAI 2015 Joint Workshop on Constraints and Preferences for Configuration and Recommendation and Intelligent Techniques for Web Personalization co-located with the 24th International Joint Conference on Artificial Intelligence (IJCAI 2015), Buenos Aires, Argentina, July 27, 2015. CEUR Workshop Proceedings 1440, CEUR-WS.org 2015 [contents] - 2014
- [c79]Yong Zheng, Bamshad Mobasher, Robin D. Burke:
Deviation-Based Contextual SLIM Recommenders. CIKM 2014: 271-280 - [c78]Jonathan Gemmell, Bamshad Mobasher, Robin D. Burke:
Resource Recommendation in Social Annotation Systems Based on User Partitioning. EC-Web 2014: 101-112 - [c77]Xavier Amatriain, Bamshad Mobasher:
The recommender problem revisited: morning tutorial. KDD 2014: 1971 - [c76]Negar Hariri, Bamshad Mobasher, Robin D. Burke:
Context adaptation in interactive recommender systems. RecSys 2014: 41-48 - [c75]Yong Zheng, Bamshad Mobasher, Robin D. Burke:
CSLIM: contextual SLIM recommendation algorithms. RecSys 2014: 301-304 - [c74]Dietmar Jannach, Jill Freyne, Werner Geyer, Ido Guy, Andreas Hotho, Bamshad Mobasher:
The sixth ACM RecSys workshop on recommender systems and the social web. RecSys 2014: 395 - [c73]Yong Zheng, Robin D. Burke, Bamshad Mobasher:
Splitting approaches for context-aware recommendation: an empirical study. SAC 2014: 274-279 - [c72]Robin D. Burke, Fatemeh Vahedian, Bamshad Mobasher:
Hybrid Recommendation in Heterogeneous Networks. UMAP 2014: 49-60 - [c71]Jonathan Gemmell, Bamshad Mobasher, Robin D. Burke:
User Partitioning Hybrid for Tag Recommendation. UMAP 2014: 74-85 - [c70]Yong Zheng, Bamshad Mobasher, Robin D. Burke:
Context Recommendation Using Multi-label Classification. WI-IAT (1) 2014: 288-295 - [p1]Negar Hariri, Carlos Castro-Herrera, Jane Cleland-Huang, Bamshad Mobasher:
Recommendation Systems in Requirements Discovery. Recommendation Systems in Software Engineering 2014: 455-476 - [e14]Jimmy Lin, Jian Pei, Xiaohua Hu, Wo Chang, Raghunath Nambiar, Charu C. Aggarwal, Nick Cercone, Vasant G. Honavar, Jun Huan, Bamshad Mobasher, Saumyadipta Pyne:
2014 IEEE International Conference on Big Data (IEEE BigData 2014), Washington, DC, USA, October 27-30, 2014. IEEE Computer Society 2014, ISBN 978-1-4799-5665-4 [contents] - [e13]Dietmar Jannach, Jill Freyne, Werner Geyer, Ido Guy, Andreas Hotho, Bamshad Mobasher:
Proceedings of the 6th Workshop on Recommender Systems and the Social Web (RSWeb 2014) co-located with the 8th ACM Conference on Recommender Systems (RecSys 2014), Foster City, CA, USA, October 6, 2014. CEUR Workshop Proceedings 1271, CEUR-WS.org 2014 [contents] - 2013
- [j33]Negar Hariri, Carlos Castro-Herrera, Mehdi Mirakhorli, Jane Cleland-Huang, Bamshad Mobasher:
Supporting Domain Analysis through Mining and Recommending Features from Online Product Listings. IEEE Trans. Software Eng. 39(12): 1736-1752 (2013) - [c69]Negar Hariri, Bamshad Mobasher, Robin D. Burke:
Query-driven context aware recommendation. RecSys 2013: 9-16 - [c68]Yong Zheng, Bamshad Mobasher, Robin D. Burke:
The Role of Emotions in Context-aware Recommendation. Decisions@RecSys 2013: 21-28 - [c67]Bamshad Mobasher, Dietmar Jannach, Werner Geyer, Jill Freyne, Andreas Hotho, Sarabjot Singh Anand, Ido Guy:
The fifth ACM RecSys workshop on recommender systems and the social web. RecSys 2013: 477-478 - [c66]Yong Zheng, Robin D. Burke, Bamshad Mobasher:
Recommendation with Differential Context Weighting. UMAP 2013: 152-164 - [e12]Bamshad Mobasher, Dietmar Jannach, Werner Geyer, Jill Freyne, Andreas Hotho, Sarabjot Singh Anand, Ido Guy:
Proceedings of the Fifth ACM RecSys Workshop on Recommender Systems and the Social Web co-located with the 7th ACM Conference on Recommender Systems (RecSys 2013), Hong Kong, China, October 13, 2013. CEUR Workshop Proceedings 1066, CEUR-WS.org 2013 [contents] - 2012
- [j32]Myra Spiliopoulou, Bamshad Mobasher, Olfa Nasraoui, Osmar R. Zaïane:
Guest editorial: special issue on a decade of mining the Web. Data Min. Knowl. Discov. 24(3): 473-477 (2012) - [j31]Jonathan Gemmell, Thomas Schimoler, Bamshad Mobasher, Robin D. Burke:
Resource recommendation in social annotation systems: A linear-weighted hybrid approach. J. Comput. Syst. Sci. 78(4): 1160-1174 (2012) - [c65]Yong Zheng, Robin D. Burke, Bamshad Mobasher:
Differential Context Relaxation for Context-Aware Travel Recommendation. EC-Web 2012: 88-99 - [c64]Collin McMillan, Negar Hariri, Denys Poshyvanyk, Jane Cleland-Huang, Bamshad Mobasher:
Recommending source code for use in rapid software prototypes. ICSE 2012: 848-858 - [c63]Negar Hariri, Bamshad Mobasher, Robin D. Burke:
Context-aware music recommendation based on latenttopic sequential patterns. RecSys 2012: 131-138 - [c62]Bamshad Mobasher, Dietmar Jannach, Werner Geyer, Andreas Hotho:
4th ACM RecSys workshop on recommender systems and the social web. RecSys 2012: 345-346 - [c61]Laura Christiansen, Thomas Schimoler, Robin D. Burke, Bamshad Mobasher:
Modeling topic trends on the social web using temporal signatures. WIDM 2012: 3-10 - [c60]Negar Hariri, Bamshad Mobasher, Robin D. Burke:
Using social tags to infer context in hybrid music recommendation. WIDM 2012: 41-48 - [e11]Bamshad Mobasher, Dietmar Jannach, Werner Geyer, Andreas Hotho:
Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web, RSWeb '12, Dublin, Ireland, September 9, 2012. ACM 2012, ISBN 978-1-4503-1638-5 [contents] - [e10]Judith Masthoff, Bamshad Mobasher, Michel C. Desmarais, Roger Nkambou:
User Modeling, Adaptation, and Personalization - 20th International Conference, UMAP 2012, Montreal, Canada, July 16-20, 2012. Proceedings. Lecture Notes in Computer Science 7379, Springer 2012, ISBN 978-3-642-31453-7 [contents] - 2011
- [j30]Gediminas Adomavicius, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin:
Context-Aware Recommender Systems. AI Mag. 32(3): 67-80 (2011) - [j29]Bamshad Mobasher, Jane Cleland-Huang:
Recommender Systems in Requirements Engineering. AI Mag. 32(3): 81-89 (2011) - [c59]Jonathan Gemmell, Thomas Schimoler, Bamshad Mobasher, Robin D. Burke:
Recommendation by Example in Social Annotation Systems. EC-Web 2011: 209-220 - [c58]Horatiu Dumitru, Marek Gibiec, Negar Hariri, Jane Cleland-Huang, Bamshad Mobasher, Carlos Castro-Herrera, Mehdi Mirakhorli:
On-demand feature recommendations derived from mining public product descriptions. ICSE 2011: 181-190 - [c57]Negar Hariri, Bamshad Mobasher, Robin Burke, Yong Zheng:
Context-Aware Recommendation Based On Review Mining. ITWP@IJCAI 2011 - [c56]Jonathan Gemmell, Thomas Schimoler, Bamshad Mobasher, Robin D. Burke:
Tag-Based Resource Recommendation in Social Annotation Applications. UMAP 2011: 111-122 - [e9]Bamshad Mobasher, Robin D. Burke, Dietmar Jannach, Gediminas Adomavicius:
Proceedings of the 2011 ACM Conference on Recommender Systems, RecSys 2011, Chicago, IL, USA, October 23-27, 2011. ACM 2011, ISBN 978-1-4503-0683-6 [contents] - 2010
- [c55]Jonathan Gemmell, Thomas Schimoler, Bamshad Mobasher, Robin D. Burke:
Hybrid tag recommendation for social annotation systems. CIKM 2010: 829-838 - [c54]Jonathan Gemmell, Thomas Schimoler, Bamshad Mobasher, Robin D. Burke:
Resource Recommendation in Collaborative Tagging Applications. EC-Web 2010: 1-12 - [c53]Ahu Sieg, Bamshad Mobasher, Robin Burke:
Improving the effectiveness of collaborative recommendation with ontology-based user profiles. HetRec@RecSys 2010: 39-46 - [c52]Werner Geyer, Jill Freyne, Bamshad Mobasher, Sarabjot S. Anand, Casey Dugan:
2nd workshop on recommender systems and the social web. RecSys 2010: 379-380 - [c51]Ahu Sieg, Bamshad Mobasher, Robin Burke:
Ontology-Based Collaborative Recommendation. ITWP@UMAP 2010 - [e8]Bamshad Mobasher, Dietmar Jannach, Sarabjot Singh Anand:
Proceedings of the 8th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems, ITWP@UMAP 2010, Big Island, HI, USA, June 20, 2010. CEUR Workshop Proceedings 606, CEUR-WS.org 2010 [contents]
2000 – 2009
- 2009
- [j28]Razvan C. Bunescu, Vitor R. Carvalho, Jan Chomicki, Vincent Conitzer, Michael T. Cox, Virginia Dignum, Zachary Dodds, Mark Dredze, David Furcy, Evgeniy Gabrilovich, Mehmet H. Göker, Hans W. Guesgen, Haym Hirsh, Dietmar Jannach, Ulrich Junker, Wolfgang Ketter, Alfred Kobsa, Sven Koenig, Tessa A. Lau, Lundy Lewis, Eric T. Matson, Ted Metzler, Rada Mihalcea, Bamshad Mobasher, Joelle Pineau, Pascal Poupart, Anita Raja, Wheeler Ruml, Norman M. Sadeh, Guy Shani, Daniel G. Shapiro, Sarabjot Singh Anand, Matthew E. Taylor, Kiri Wagstaff, Trey Smith, William E. Walsh, Rong Zhou:
AAAI 2008 Workshop Reports. AI Mag. 30(1): 108-118 (2009) - [j27]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) - [c50]Maryam Ramezani, Jeff J. Sandvig, Thomas Schimoler, Jonathan Gemmell, Bamshad Mobasher, Robin D. Burke:
Evaluating the Impact of Attacks in Collaborative Tagging Environments. CSE (4) 2009: 136-143 - [c49]Jonathan Gemmell, Thomas Schimoler, Maryam Ramezani, Bamshad Mobasher:
Adapting K-Nearest Neighbor for Tag Recommendation in Folksonomies. ITWP 2009 - [c48]Jonathan Gemmell, Maryam Ramezani, Thomas Schimoler, Laura Christiansen, Bamshad Mobasher:
A Fast Effective Multi-Channeled Tag Recommender. DC@PKDD/ECML 2009 - [c47]Carlos Castro-Herrera, Jane Cleland-Huang, Bamshad Mobasher:
Enhancing Stakeholder Profiles to Improve Recommendations in Online Requirements Elicitation. RE 2009: 37-46 - [c46]Jonathan Gemmell, Maryam Ramezani, Thomas Schimoler, Laura Christiansen, Bamshad Mobasher:
The impact of ambiguity and redundancy on tag recommendation in folksonomies. RecSys 2009: 45-52 - [c45]Carlos Castro-Herrera, Jane Cleland-Huang, Bamshad Mobasher:
A recommender system for dynamically evolving online forums. RecSys 2009: 213-216 - [c44]Dietmar Jannach, Werner Geyer, Casey Dugan, Jill Freyne, Sarabjot S. Anand, Bamshad Mobasher, Alfred Kobsa:
Workshop on recommender systems and the social web. RecSys 2009: 421-422 - [c43]Carlos Castro-Herrera, Chuan Duan, Jane Cleland-Huang, Bamshad Mobasher:
A recommender system for requirements elicitation in large-scale software projects. SAC 2009: 1419-1426 - [e7]Sarabjot S. Anand, Bamshad Mobasher, Alfred Kobsa, Dietmar Jannach:
Proceedings of the 7th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems (ITWP'09), Pasadena, California, USA, July 11-17, 2009 in conjunction with the 21st International Joint Conference on Artificial Intelligence - IJCAI 2009. CEUR Workshop Proceedings 528, CEUR-WS.org 2009 [contents] - [e6]Haizheng Zhang, Myra Spiliopoulou, Bamshad Mobasher, C. Lee Giles, Andrew McCallum, Olfa Nasraoui, Jaideep Srivastava, John Yen:
Advances in Web Mining and Web Usage Analysis, 9th International Workshop on Knowledge Discovery on the Web, WebKDD 2007, and 1st International Workshop on Social Networks Analysis, SNA-KDD 2007, San Jose, CA, USA, August 12-15, 2007. Revised Papers. Lecture Notes in Computer Science 5439, Springer 2009, ISBN 978-3-642-00527-5 [contents] - [r2]Bamshad Mobasher:
Web Mining Overview. Encyclopedia of Data Warehousing and Mining 2009: 2085-2089 - 2008
- [j26]Jeff J. Sandvig, Bamshad Mobasher, Robin D. Burke:
A Survey of Collaborative Recommendation and the Robustness of Model-Based Algorithms. IEEE Data Eng. Bull. 31(2): 3-13 (2008) - [j25]Olfa Nasraoui, Myra Spiliopoulou, Osmar R. Zaïane, Jaideep Srivastava, Bamshad Mobasher:
WebKDD 2008: 10 years of knowledge discovery on the web post-workshop report. SIGKDD Explor. 10(2): 78-83 (2008) - [c42]Chuan Duan, Jane Cleland-Huang, Bamshad Mobasher:
A consensus based approach to constrained clustering of software requirements. CIKM 2008: 1073-1082 - [c41]Jonathan Gemmell, Andriy Shepitsen, Bamshad Mobasher, Robin D. Burke:
Personalizing Navigation in Folksonomies Using Hierarchical Tag Clustering. DaWaK 2008: 196-205 - [c40]Jane Cleland-Huang, Bamshad Mobasher:
Using data mining and recommender systems to scale up the requirements process. ULSSIS@ICSE 2008: 3-6 - [c39]Lawrence D. Bergman, Jihie Kim, Bamshad Mobasher, Stefan M. Rüger, Stefan Siersdorfer, Sergej Sizov, Markus Stolze:
International workshop on recommendation and collaboration (ReColl 2008). IUI 2008: 439 - [c38]Carlos Castro-Herrera, Chuan Duan, Jane Cleland-Huang, Bamshad Mobasher:
Using Data Mining and Recommender Systems to Facilitate Large-Scale, Open, and Inclusive Requirements Elicitation Processes. RE 2008: 165-168 - [c37]Andriy Shepitsen, Jonathan Gemmell, Bamshad Mobasher, Robin D. Burke:
Personalized recommendation in social tagging systems using hierarchical clustering. RecSys 2008: 259-266 - [e5]Pearl Pu, Derek G. Bridge, Bamshad Mobasher, Francesco Ricci:
Proceedings of the 2008 ACM Conference on Recommender Systems, RecSys 2008, Lausanne, Switzerland, October 23-25, 2008. ACM 2008, ISBN 978-1-60558-093-7 [contents] - 2007
- [j24]Sarabjot Singh Anand, Daniel Bahls, Catherina Burghart, Mark H. Burstein, Huajun Chen, John Collins, Thomas G. Dietterich, Jon Doyle, Chris Drummond, William Elazmeh, Christopher W. Geib, Judy Goldsmith, Hans W. Guesgen, Jim Hendler, Dietmar Jannach, Nathalie Japkowicz, Ulrich Junker, Gal A. Kaminka, Alfred Kobsa, Jérôme Lang, David B. Leake, Lundy Lewis, Gerard Ligozat, Sofus A. Macskassy, Drew V. McDermott, Ted Metzler, Bamshad Mobasher, Ullas Nambiar, Zaiqing Nie, Klas Orsvärn, Barry O'Sullivan, David V. Pynadath, Jochen Renz, Rita V. Rodríguez, Thomas Roth-Berghofer, Stefan Schulz, Rudi Studer, Yimin Wang, Michael P. Wellman:
AAAI-07 Workshop Reports. AI Mag. 28(4): 119-128 (2007) - [j23]Ahu Sieg, Bamshad Mobasher, Robin D. Burke:
Learning Ontology-Based User Profiles: A Semantic Approach to Personalized Web Search. IEEE Intell. Informatics Bull. 8(1): 7-18 (2007) - [j22]Bamshad Mobasher, Robin D. Burke, Runa Bhaumik, Jeff J. Sandvig:
Attacks and Remedies in Collaborative Recommendation. IEEE Intell. Syst. 22(3): 56-63 (2007) - [j21]Bamshad Mobasher:
Recommender Systems. Künstliche Intell. 21(3): 41-43 (2007) - [j20]Haizheng Zhang, John Yen, C. Lee Giles, Bamshad Mobasher, Myra Spiliopoulou, Jaideep Srivastava, Olfa Nasraoui, Andrew McCallum:
WebKDD/SNAKDD 2007: web mining and social network analysis post-workshop report. SIGKDD Explor. 9(2): 87-92 (2007) - [j19]Chad Williams, Bamshad Mobasher, Robin D. Burke:
Defending recommender systems: detection of profile injection attacks. Serv. Oriented Comput. Appl. 1(3): 157-170 (2007) - [j18]Sarabjot S. Anand, Bamshad Mobasher:
Introduction to intelligent techniques for Web personalization. ACM Trans. Internet Techn. 7(4): 18 (2007) - [j17]Bamshad Mobasher, Robin D. Burke, Runa Bhaumik, Chad Williams:
Toward trustworthy recommender systems: An analysis of attack models and algorithm robustness. ACM Trans. Internet Techn. 7(4): 23 (2007) - [c36]Bamshad Mobasher:
Data Mining for Web Personalization. The Adaptive Web 2007: 90-135 - [c35]Ahu Sieg, Bamshad Mobasher, Robin D. Burke:
Web search personalization with ontological user profiles. CIKM 2007: 525-534 - [c34]Ahu Sieg, Bamshad Mobasher, Robin D. Burke:
Representing Context in Web Search with Ontological User Profiles. CONTEXT 2007: 439-452 - [c33]Runa Bhaumik, Robin D. Burke, Bamshad Mobasher:
Crawling Attacks Against Web-based Recommender Systems. DMIN 2007: 183-189 - [c32]Jeff J. Sandvig, Bamshad Mobasher, Robin D. Burke:
Impact of Relevance Measures on the Robustness and Accuracy of Collaborative Filtering. EC-Web 2007: 99-108 - [c31]Ahu Sieg, Bamshad Mobasher, Robin D. Burke:
Ontological User Profiles for Representing Context in Web Search. Web Intelligence/IAT Workshops 2007: 91-94 - [c30]Jeff J. Sandvig, Bamshad Mobasher, Robin D. Burke:
Robustness of collaborative recommendation based on association rule mining. RecSys 2007: 105-112 - [e4]Olfa Nasraoui, Myra Spiliopoulou, Jaideep Srivastava, Bamshad Mobasher, Brij M. Masand:
Advances in Web Mining and Web Usage Analysis, 8th International Workshop on Knowledge Discovery on the Web, WebKDD 2006, Philadelphia, PA, USA, August 20, 2006, Revised Papers. Lecture Notes in Computer Science 4811, Springer 2007, ISBN 978-3-540-77484-6 [contents] - 2006
- [j16]Wolfgang Achtner, Esma Aïmeur, Sarabjot Singh Anand, Douglas E. Appelt, Naveen Ashish, Tiffany Barnes, Joseph E. Beck, M. Bernardine Dias, Prashant Doshi, Chris Drummond, William Elazmeh, Ariel Felner, Dayne Freitag, Hector Geffner, Christopher W. Geib, Richard Goodwin, Robert C. Holte, Frank Hutter, Fair Isaac, Nathalie Japkowicz, Gal A. Kaminka, Sven Koenig, Michail G. Lagoudakis, David B. Leake, Lundy Lewis, Hugo Liu, Ted Metzler, Rada Mihalcea, Bamshad Mobasher, Pascal Poupart, David V. Pynadath, Thomas Roth-Berghofer, Wheeler Ruml, Stefan Schulz, Sven Schwarz, Stephanie Seneff, Amit P. Sheth, Ron Sun, Michael Thielscher, Afzal Upal, Jason D. Williams, Steve J. Young, Dmitry Zelenko:
Reports on the Twenty-First National Conference on Artificial Intelligence (AAAI-06) Workshop Program. AI Mag. 27(4): 92-102 (2006) - [j15]Olfa Nasraoui, Myra Spiliopoulou, Jaideep Srivastava, Bamshad Mobasher, Brij M. Masand:
WebKDD 2006: web mining and web usage analysis post-workshop report. SIGKDD Explor. 8(2): 84-89 (2006) - [c29]Bamshad Mobasher, Robin D. Burke, Jeff J. Sandvig:
Model-Based Collaborative Filtering as a Defense against Profile Injection Attacks. AAAI 2006: 1388-1393 - [c28]Yanzan Zhou, Bamshad Mobasher:
Web User Segmentation Based on a Mixture of Factor Analyzers. EC-Web 2006: 11-20 - [c27]Chad Williams, Bamshad Mobasher, Robin D. Burke, Runa Bhaumik:
Detecting Profile Injection Attacks in Collaborative Filtering: A Classification-Based Approach. WEBKDD 2006: 167-186 - [c26]Robin D. Burke, Bamshad Mobasher, Chad Williams, Runa Bhaumik:
Classification features for attack detection in collaborative recommender systems. KDD 2006: 542-547 - [c25]Sarabjot S. Anand, Bamshad Mobasher:
Contextual Recommendation. WebMine 2006: 142-160 - [c24]Robin D. Burke, Bamshad Mobasher, Chad Williams, Runa Bhaumik:
Detecting Profile Injection Attacks in Collaborative Recommender Systems. CEC/EEE 2006: 23 - [e3]Bamshad Mobasher, Olfa Nasraoui, Bing Liu, Brij M. Masand:
Advances in Web Mining and Web Usage Analysis, 6th International Workshop on Knowledge Discovery on the Web, WebKDD 2004, Seattle, WA, USA, August 22-25, 2004, Revised Selected Papers. Lecture Notes in Computer Science 3932, Springer 2006, ISBN 978-3-540-47127-1 [contents] - [e2]Olfa Nasraoui, Osmar R. Zaïane, Myra Spiliopoulou, Bamshad Mobasher, Brij M. Masand, Philip S. Yu:
Advances in Web Mining and Web Usage Analysis, 7th International Workshop on Knowledge Discovery on the Web, WebKDD 2005, Chicago, IL, USA, August 21, 2005. Revised Papers. Lecture Notes in Computer Science 4198, Springer 2006, ISBN 3-540-46346-1 [contents] - 2005
- [j14]Ion Muslea, Virginia Dignum, Daniel D. Corkill, Catholijn M. Jonker, Frank Dignum, Silvia Coradeschi, Alessandro Saffiotti, Dan Fu, Jeff Orkin, William Cheetham, Kai Goebel, Piero P. Bonissone, Leen-Kiat Soh, Randolph M. Jones, Robert E. Wray III, Matthias Scheutz, Daniela Pucci de Farias, Shie Mannor, Georgios Theocharous, Doina Precup, Bamshad Mobasher, Sarabjot S. Anand, Bettina Berendt, Andreas Hotho, Hans W. Guesgen, Michael T. Rosenstein, Mohammad Ghavamzadeh:
The Workshop Program at the Nineteenth National Conference on Artificial Intelligence. AI Mag. 26(1): 103-108 (2005) - [j13]Olfa Nasraoui, Osmar R. Zaïane, Myra Spiliopoulou, Bamshad Mobasher, Brij M. Masand, Philip S. Yu:
WebKDD 2005: web mining and web usage analysis post-workshop report. SIGKDD Explor. 7(2): 139-142 (2005) - [c23]Robin D. Burke, Bamshad Mobasher, Runa Bhaumik, Chad Williams:
Segment-Based Injection Attacks against Collaborative Filtering Recommender Systems. ICDM 2005: 577-580 - [c22]Xin Jin, Bamshad Mobasher, Yanzan Zhou:
A Web Recommendation System Based on Maximum Entropy. ITCC (1) 2005: 213-218 - [c21]Bamshad Mobasher, Robin D. Burke, Chad Williams, Runa Bhaumik:
Analysis and Detection of Segment-Focused Attacks Against Collaborative Recommendation. WEBKDD 2005: 96-118 - [c20]Xin Jin, Yanzan Zhou, Bamshad Mobasher:
A maximum entropy web recommendation system: combining collaborative and content features. KDD 2005: 612-617 - [c19]Xin Jin, Yanzan Zhou, Bamshad Mobasher:
Task-Oriented Web User Modeling for Recommendation. User Modeling 2005: 109-118 - [e1]Bamshad Mobasher, Sarabjot S. Anand:
Intelligent Techniques for Web Personalization, IJCAI 2003 Workshop, ITWP 2003, Acapulco, Mexico, August 11, 2003, Revised Selected Papers. Lecture Notes in Computer Science 3169, Springer 2005, ISBN 3-540-29846-0 [contents] - 2004
- [j12]Olfa Nasraoui, Bamshad Mobasher, Brij M. Masand, Bing Liu:
WebKDD 2004: web mining and web usage analysis post-workshop report. SIGKDD Explor. 6(2): 147-151 (2004) - [c18]Xin Jin, Yanzan Zhou, Bamshad Mobasher:
Web usage mining based on probabilistic latent semantic analysis. KDD 2004: 197-205 - [c17]Yanzan Zhou, Xin Jin, Bamshad Mobasher:
A Recommendation Model Based on Latent Principal Factors in Web Navigation Data. WebDyn@WWW 2004: 52-61 - [r1]Bamshad Mobasher:
Web Usage Mining and Personalization. The Practical Handbook of Internet Computing 2004 - 2003
- [j11]Myra Spiliopoulou, Bamshad Mobasher, Bettina Berendt, Miki Nakagawa:
A Framework for the Evaluation of Session Reconstruction Heuristics in Web-Usage Analysis. INFORMS J. Comput. 15(2): 171-190 (2003) - [c16]Bamshad Mobasher, Xin Jin, Yanzan Zhou:
Semantically Enhanced Collaborative Filtering on the Web. EWMF 2003: 57-76 - [c15]Honghua (Kathy) Dai, Bamshad Mobasher:
A Road Map to More Effective Web Personalization: Integrating Domain Knowledge with Web Usage Mining. International Conference on Internet Computing 2003: 58-64 - [c14]Ahu Sieg, Bamshad Mobasher, Steven L. Lytinen, Robin D. Burke:
Concept Based Query Enhancement in the ARCH Search Agent. International Conference on Internet Computing 2003: 613-619 - [c13]Sarabjot S. Anand, Bamshad Mobasher:
Intelligent Techniques for Web Personalization. ITWP 2003: 1-36 - 2002
- [j10]Bamshad Mobasher, Honghua Dai, Tao Luo, Miki Nakagawa:
Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization. Data Min. Knowl. Discov. 6(1): 61-82 (2002) - [c12]Bamshad Mobasher, Honghua Dai, Tao Luo, Miki Nakagawa:
Using Sequential and Non-Sequential Patterns in Predictive Web Usage Mining Tasks. ICDM 2002: 669-672 - [c11]Bettina Berendt, Bamshad Mobasher, Miki Nakagawa, Myra Spiliopoulou:
The Impact of Site Structure and User Environment on Session Reconstruction in Web Usage Analysis. WEBKDD 2002: 159-179 - 2001
- [j9]John Collins, Corey Bilot, Maria L. Gini, Bamshad Mobasher:
Decision Processes in Agent-Based Automated Contracting. IEEE Internet Comput. 5(2): 61-72 (2001) - [c10]Bamshad Mobasher, Honghua Dai, Tao Luo, Miki Nakagawa:
Effective personalization based on association rule discovery from web usage data. WIDM 2001: 9-15 - 2000
- [j8]Bamshad Mobasher, Robert Cooley, Jaideep Srivastava:
Automatic personalization based on Web usage mining. Commun. ACM 43(8): 142-151 (2000) - [c9]Bamshad Mobasher, Honghua Dai, Tao Luo, Yuqing Sun, Jiang Zhu:
Integrating Web Usage and Content Mining for More Effective Personalization. EC-Web 2000: 165-176
1990 – 1999
- 1999
- [j7]Daniel Boley, Maria L. Gini, Robert Gross, Eui-Hong Han, Kyle Hastings, George Karypis, Vipin Kumar, Bamshad Mobasher, Jerome Moore:
Document Categorization and Query Generation on the World Wide Web Using WebACE. Artif. Intell. Rev. 13(5-6): 365-391 (1999) - [j6]Daniel Boley, Maria L. Gini, Robert Gross, Eui-Hong Han, Kyle Hastings, George Karypis, Vipin Kumar, Bamshad Mobasher, Jerome Moore:
Partitioning-based clustering for Web document categorization. Decis. Support Syst. 27(3): 329-341 (1999) - [j5]Robert Cooley, Bamshad Mobasher, Jaideep Srivastava:
Data Preparation for Mining World Wide Web Browsing Patterns. Knowl. Inf. Syst. 1(1): 5-32 (1999) - [c8]John Collins, Maksim Tsvetovat, Rashmi Sundareswara, Joshua van Tonder, Maria L. Gini, Bamshad Mobasher:
Evaluating Risk: Flexibility and Feasibility in Multi-Agent Contracting. Agents 1999: 350-351 - [c7]John Collins, Rashmi Sundareswara, Maria L. Gini, Bamshad Mobasher:
Bid Selection Strategies for Multi-agent Contracting in the Presence of Scheduling Constraints. Agent Mediated Electronic Commerce (IJCAI Workshop) 1999: 113-130 - 1998
- [j4]Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad Mobasher:
Hypergraph Based Clustering in High-Dimensional Data Sets: A Summary of Results. IEEE Data Eng. Bull. 21(1): 15-22 (1998) - [j3]Daniel Boley, Maria L. Gini, Kyle Hastings, Bamshad Mobasher, Jerry Moore:
A client-side Web agent for document categorization. Internet Res. 8(5): 387-399 (1998) - [c6]John Collins, Ben Youngdahl, Scott Jamison, Bamshad Mobasher, Maria L. Gini:
A Market Architecture for Multi-Agent Contracting. Agents 1998: 285-292 - [c5]Eui-Hong Han, Daniel Boley, Maria L. Gini, Robert Gross, Kyle Hastings, George Karypis, Vipin Kumar, Bamshad Mobasher, Jerome Moore:
WebACE: A Web Agent for Document Categorization and Exploration. Agents 1998: 408-415 - [c4]Erik S. Steinmetz, John Collins, Scott Jamison, Rashmi Sundareswara, Bamshad Mobasher, Maria L. Gini:
Bid Evaluation and Selection in the MAGNET Automated Contracting System. AMET 1998: 105-125 - 1997
- [j2]Maksim Tsvetovatyy, Maria L. Gini, Bamshad Mobasher, Zbigniew Wieckowski:
Magma: An Agent Based Virtual Market for Electronic Commerce. Appl. Artif. Intell. 11(6): 501-523 (1997) - [j1]Bamshad Mobasher, Don Pigozzi, Giora Slutzki:
Multi-Valued Logic Programming Semantics: An Algebraic Approach. Theor. Comput. Sci. 171(1-2): 77-109 (1997) - [c3]Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad Mobasher:
Clustering Based On Association Rule Hypergraphs. DMKD 1997 - [c2]Robert Cooley, Bamshad Mobasher, Jaideep Srivastava:
Web Mining: Information and Pattern Discovery on the World Wide Web. ICTAI 1997: 558-567 - 1993
- [c1]Bamshad Mobasher, Jacek Leszczylowski, Don Pigozzi:
Negation as Partial Failure. LPNMR 1993: 244-262
Coauthor Index
Sarabjot S. Anand
aka: Sarabjot Singh Anand
aka: Sarabjot Singh Anand
Robin D. Burke
aka: Robin Burke
aka: Robin Burke
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