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Bamshad Mobasher

1993–2026 年に発表

257
論文数
18,573
被引用数
65
h 指数
157
i10 指数

被引用数

Bamshad Mobasher の年別被引用数1996 年: 被引用 1 件1997 年: 被引用 14 件1998 年: 被引用 28 件1999 年: 被引用 71 件2000 年: 被引用 110 件2001 年: 被引用 154 件2002 年: 被引用 278 件2003 年: 被引用 379 件2004 年: 被引用 457 件2005 年: 被引用 426 件2006 年: 被引用 437 件2007 年: 被引用 465 件2008 年: 被引用 360 件2009 年: 被引用 506 件2010 年: 被引用 522 件2011 年: 被引用 590 件2012 年: 被引用 588 件2013 年: 被引用 560 件2014 年: 被引用 610 件2015 年: 被引用 678 件2016 年: 被引用 585 件2017 年: 被引用 589 件2018 年: 被引用 655 件2019 年: 被引用 587 件2020 年: 被引用 536 件2021 年: 被引用 623 件2022 年: 被引用 415 件2023 年: 被引用 430 件2024 年: 被引用 405 件2025 年: 被引用 306 件2026 年: 被引用 76 件

引用元

国・地域

この著者を引用した国・地域の世界地図アメリカ合衆国: 引用元論文 1,851 件、この内訳の 18%中国: 引用元論文 1,421 件、この内訳の 13.8%イタリア: 引用元論文 499 件、この内訳の 4.8%イギリス: 引用元論文 420 件、この内訳の 4.1%ドイツ: 引用元論文 413 件、この内訳の 4%インド: 引用元論文 391 件、この内訳の 3.8%オーストラリア: 引用元論文 376 件、この内訳の 3.7%スペイン: 引用元論文 359 件、この内訳の 3.5%カナダ: 引用元論文 345 件、この内訳の 3.3%フランス: 引用元論文 326 件、この内訳の 3.2%台湾: 引用元論文 256 件、この内訳の 2.5%韓国: 引用元論文 249 件、この内訳の 2.4%
0%18%その他 32.9%

機関

分野

  • Computer Science83.3%
  • Social Sciences4.4%
  • Decision Sciences3.1%
  • Physics and Astronomy2.5%
  • Business, Management and Accounting2.5%
  • Engineering1.3%
  • その他2.9%

トピック

  • Recommender Systems and Techniques17.6%
  • Web Data Mining and Analysis4.9%
  • Data Mining Algorithms and Applications4.2%
  • Data Management and Algorithms3.7%
  • Advanced Bandit Algorithms Research2.8%
  • Caching and Content Delivery2.6%
  • その他64.2%

共著者

全論文

検索で開く
  1. Controlling Popularity Bias in Learning-to-Rank Recommendation

    著者: Himan Abdollahpouri, Robin Burke, Bamshad Mobasher - Eleventh ACM Conference on Recommender Systems, RecSys 2017 被引用: 420

  2. User-centered Evaluation of Popularity Bias in Recommender Systems

    著者: Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher, Edward C. Malthouse - Conference on User Modeling, UMAP 2021 被引用: 137

  3. A Graph-Based Approach for Mitigating Multi-Sided Exposure Bias in Recommender Systems

    著者: Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke - ACM Transactions on Information Systems, ACM Trans. Inf. Syst. 2021 被引用: 66

  4. Toward trustworthy recommender systems: An analysis of attack models and algorithm robustness

    著者: Bamshad Mobasher, Robin Burke, Runa Bhaumik, Chad Williams - ACM Transactions on Internet Technology, ACM Trans. Internet Techn. 2007 被引用: 465

  5. Managing Popularity Bias in Recommender Systems with Personalized Re-Ranking

    著者: Himan Abdollahpouri, Robin Burke, Bamshad Mobasher - FLAIRS 2019 被引用: 107

  6. The Unfairness of Popularity Bias in Recommendation

    著者: Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher - RMSE@RecSys 2019 被引用: 281

  7. Unbiased Cascade Bandits: Mitigating Exposure Bias in Online Learning to Rank Recommendation

    著者: Masoud Mansoury, Himan Abdollahpouri, Bamshad Mobasher, Mykola Pechenizkiy, Robin Burke, Milad Sabouri - arXiv (Cornell University), CoRR 2021 被引用: 27

  8. Feedback Loop and Bias Amplification in Recommender Systems

    著者: Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke - International Conference on Information & Knowledge Management, CIKM 2020 被引用: 42

  9. 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

    著者: Olfa Nasraoui, Myra Spiliopoulou, Jaideep Srivastava, Bamshad Mobasher, Brij M. Masand - Lecture notes in computer science, WebKDD 2007 被引用: 34

  10. Context-Aware Recommender Systems

    著者: Gediminas Adomavicius, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin - AI Magazine, AI Mag. 2011 被引用: 1,365

  11. Classification features for attack detection in collaborative recommender systems

    著者: Robin D. Burke, Bamshad Mobasher, Chad Williams, Runa Bhaumik - SIGKDD international conference on Knowledge discovery and data mining 2006 被引用: 251

  12. Context-aware music recommendation based on latenttopic sequential patterns

    著者: Negar Hariri, Bamshad Mobasher, Robin D. Burke - sixth ACM conference on Recommender systems, RecSys 2012 被引用: 314

  13. Personalized recommendation in social tagging systems using hierarchical clustering

    著者: Andriy Shepitsen, Jonathan Gemmell, Bamshad Mobasher, Robin D. Burke - conference on Recommender systems, RecSys 2008 被引用: 527

  14. Defending recommender systems: detection of profile injection attacks

    著者: Chad Williams, Bamshad Mobasher, Robin D. Burke - Service Oriented Computing and Applications, Serv. Oriented Comput. Appl. 2007 被引用: 157

  15. Calibration in Collaborative Filtering Recommender Systems: a User-Centered Analysis

    著者: Kun Lin, Nasim Sonboli, Bamshad Mobasher, Robin Burke - Conference on Hypertext and Social Media, HT 2020 被引用: 24

  16. Adapting Recommendations to Contextual Changes Using Hierarchical Hidden Markov Models

    著者: Mehdi Hosseinzadeh Aghdam, Negar Hariri, Bamshad Mobasher, Robin D. Burke - Conference on Recommender Systems, RecSys 2015 被引用: 64

  17. RecSys'11 - Proceedings of the 5th ACM Conference on Recommender Systems

    著者: Robin Burke, Bamshad Mobasher, Dietmar Jannach, Gediminas Adomavičius, Yehuda Koren, Verus Pronk - 2011 被引用: 69

  18. Using Stable Matching to Optimize the Balance between Accuracy and Diversity in Recommendation

    著者: Farzad Eskandanian, Bamshad Mobasher - Conference on User Modeling, UMAP 2020 被引用: 20

  19. Web search personalization with ontological user profiles

    著者: Ahu Sieg, Bamshad Mobasher, Robin D. Burke - sixteenth ACM conference on Conference on information and knowledge management, CIKM 2007 被引用: 320

  20. A Clustering Approach for Personalizing Diversity in Collaborative Recommender Systems

    著者: Farzad Eskandanian, Bamshad Mobasher, Robin Burke - Conference on User Modeling, UMAP 2017 被引用: 52

  21. Research directions in session-based and sequential recommendation

    著者: Dietmar Jannach, Bamshad Mobasher, Shlomo Berkovsky - User Modeling and User-Adapted Interaction, User Model. User Adapt. Interact. 2020 被引用: 41

  22. The Impact of Popularity Bias on Fairness and Calibration in Recommendation

    著者: Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher - arXiv (Cornell University), CoRR 2019 被引用: 23

  23. The Connection Between Popularity Bias, Calibration, and Fairness in Recommendation

    著者: Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher - Fourteenth ACM Conference on Recommender Systems, RecSys 2020 被引用: 19

  24. Does the User Have A Theory of the Recommender? A Grounded Theory Study

    著者: Mohammed Muheeb Ghori, Arman Dehpanah, Jonathan Gemmell, Hamed Qahri-Saremi, Bamshad Mobasher - Adjunct Proceedings of the 30th ACM Conference on User Modeling, UMAP (Adjunct Publication) 2022 被引用: 16