World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
83
Citations
79438
World Ranking
874
National Ranking
476

Research.com Recognitions

  • 2013 - IEEE Fellow For contributions to human-computer interaction and social media applications
  • 2011 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2010 - ACM Software System Award For the GroupLens Collaborative Filtering Recommender Systems, which showed how to automate the process by which a distributed set of users could receive personalized recommendations by sharing ratings, leading to both commercial products and extensive research.
  • 2009 - Fellow of the American Academy of Arts and Sciences
  • 2008 - ACM Fellow For contributions to human-computer interaction.
  • 2006 - ACM Distinguished Member

Overview

Joseph A. Konstan is affiliated with the University of Minnesota in the United States. Their research spans several fields, primarily within Computer Science and Social Sciences. The main subfields of study include Information Systems, Communication, Information Systems and Management, Artificial Intelligence, and Sociology and Political Science.

The research topics covered by Joseph A. Konstan focus on Personal Information Management and User Behavior, Recommender Systems and Techniques, Advanced Bandit Algorithms Research, Knowledge Management and Sharing, Topic Modeling, Consumer Market Behavior and Pricing, and Team Dynamics and Performance.

Joseph A. Konstan has published in a variety of venues with repeated contributions to some, including:

  • arXiv (Cornell University)
  • Proceedings of the ACM on Human-Computer Interaction
  • Communications of the ACM
  • International Journal of Human-Computer Interaction
  • Continence

The scientist has collaborated frequently with coauthors such as Ruoyan Kong, Ruixuan Sun, Haiyi Zhu, Loren Terveen, and Avinash Akella.

Some recent prominent papers authored by Joseph A. Konstan include:

  • "Six Human-Centered Artificial Intelligence Grand Challenges," 2023, International Journal of Human-Computer Interaction
  • "Evolution of Experts in Question Answering Communities," 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • "Challenges and Future Directions of Computational Advertising Measurement Systems," 2020, Journal of Advertising
  • "Human-centered recommender systems: Origins, advances, challenges, and opportunities," 2021, AI Magazine
  • "Toward the Next Generation of News Recommender Systems," 2021, Companion Proceedings of the Web Conference 2021

Joseph A. Konstan has received several awards, including:

  • IEEE Fellow in 2013, for contributions to human-computer interaction and social media applications
  • Fellow of the American Association for the Advancement of Science (AAAS) in 2011
  • ACM Software System Award in 2010, for the GroupLens Collaborative Filtering Recommender Systems which demonstrated automated personalized recommendations via user rating sharing
  • Fellow of the American Academy of Arts and Sciences in 2009
  • ACM Fellow in 2008, for contributions to human-computer interaction
  • ACM Distinguished Member in 2006

Best Publications

  • Item-based collaborative filtering recommendation algorithms

    Badrul Sarwar;George Karypis;Joseph Konstan;John Riedl

  • Evaluating collaborative filtering recommender systems

    Jonathan L. Herlocker;Joseph A. Konstan;Loren G. Terveen;John T. Riedl

  • The MovieLens Datasets: History and Context

    F. Maxwell Harper;Joseph A. Konstan

  • An algorithmic framework for performing collaborative filtering

    Jonathan L. Herlocker;Joseph A. Konstan;Al Borchers;John Riedl

  • GroupLens: applying collaborative filtering to Usenet news

    Joseph A. Konstan;Bradley N. Miller;David Maltz;Jonathan L. Herlocker

  • Analysis of recommendation algorithms for e-commerce

    Badrul Sarwar;George Karypis;Joseph Konstan;John Riedl

  • E-Commerce Recommendation Applications

    J. Ben Schafer;Joseph A. Konstan;John Riedl

  • Recommender systems in e-commerce

    J. Ben Schafer;Joseph Konstan;John Riedl

  • An algorithmic framework for performing collaborative filtering

    Unknown

  • Explaining collaborative filtering recommendations

    Jonathan L. Herlocker;Joseph A. Konstan;John Riedl

  • Improving recommendation lists through topic diversification

    Cai-Nicolas Ziegler;Sean M. McNee;Joseph A. Konstan;Georg Lausen

  • Application of Dimensionality Reduction in Recommender System - A Case Study

    Badrul Sarwar;George Karypis;Joseph Konstan;John T. Riedl

  • Collaborative Filtering Recommender Systems

    Michael D. Ekstrand;John T. Riedl;Joseph A. Konstan

  • Being accurate is not enough: how accuracy metrics have hurt recommender systems

    Sean M. McNee;John Riedl;Joseph A. Konstan

  • Combining collaborative filtering with personal agents for better recommendations

    Nathaniel Good;J. Ben Schafer;Joseph A. Konstan;Al Borchers

  • Recommender systems: from algorithms to user experience

    Joseph A. Konstan;John Riedl

  • An Empirical Analysis of Design Choices in Neighborhood-Based Collaborative Filtering Algorithms

    Jon Herlocker;Joseph A. Konstan;John Riedl

  • Building Successful Online Communities: Evidence-Based Social Design

    Robert E. Kraut;Paul Resnick;Sara Kiesler;Yuqing Ren

  • Getting to know you: learning new user preferences in recommender systems

    Al Mamunur Rashid;Istvan Albert;Dan Cosley;Shyong K. Lam

  • MovieLens unplugged: experiences with an occasionally connected recommender system

    Bradley N. Miller;Istvan Albert;Shyong K. Lam;Joseph A. Konstan

  • Is seeing believing?: how recommender system interfaces affect users' opinions

    Dan Cosley;Shyong K. Lam;Istvan Albert;Joseph A. Konstan

Frequent Co-Authors

John Riedl
John Riedl University of Minnesota
Loren Terveen
Loren Terveen University of Minnesota
Brian P. Bailey
Brian P. Bailey University of Illinois at Urbana-Champaign
B. R. Simon Rosser
B. R. Simon Rosser University of Minnesota
Keith J. Horvath
Keith J. Horvath San Diego State University
Robert E. Kraut
Robert E. Kraut Carnegie Mellon University
George Karypis
George Karypis University of Minnesota
Brent Hecht
Brent Hecht Northwestern University
Gediminas Adomavicius
Gediminas Adomavicius University of Minnesota
Ed H. Chi
Ed H. Chi Google (United States)

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