2026 John Riedl: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	National Ranking	Publications	Citations
Computer Science	78	1159	613	210	79531

Discipline name

D-Index

World Ranking

National Ranking

Publications

Citations

Computer Science

1159

613

210

79531

Research.com Recognitions

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 - ACM Fellow For contributions to recommender systems and to social and collaborative computing.
2007 - ACM Distinguished Member

Overview

John Riedl was affiliated with the University of Minnesota in the United States. Their research was positioned within the field of Computer Science, focusing specifically on Artificial Intelligence.

Their work frequently addressed topics related to advanced text analysis techniques.

John Riedl authored papers published in venues such as:

Proceedings of the International AAAI Conference on Web and Social Media

One of their recent papers included:

War Versus Inspirational in Forrest Gump: Cultural Effects in Tagging Communities (2021), published in Proceedings of the International AAAI Conference on Web and Social Media

The scientist collaborated with several co-authors, including:

Zhenhua Dong
Chuan Shi
Shilad Sen
Loren Terveen

John Riedl received recognition in the form of awards. These included:

ACM Software System Award in 2010, awarded for the GroupLens Collaborative Filtering Recommender Systems, which demonstrated automating personalized recommendations by sharing user ratings, influencing both commercial products and research.
ACM Fellow in 2009, recognized for contributions to recommender systems and social and collaborative computing.
ACM Distinguished Member in 2007.

Best Publications

Item-based collaborative filtering recommendation algorithms

Badrul Sarwar;George Karypis;Joseph Konstan;John Riedl

12555
Citations
GroupLens: An Open Architecture for Collaborative Filtering of Netnews

Paul Resnick;Neophytos Iacovou;Mitesh Suchak;Peter Bergstrom

8495
Citations
Evaluating collaborative filtering recommender systems

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

7942
Citations
An algorithmic framework for performing collaborative filtering

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

4249
Citations
GroupLens: applying collaborative filtering to Usenet news

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

3906
Citations
Analysis of recommendation algorithms for e-commerce

Badrul Sarwar;George Karypis;Joseph Konstan;John Riedl

2962
Citations
E-Commerce Recommendation Applications

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

2759
Citations
Recommender systems in e-commerce

J. Ben Schafer;Joseph Konstan;John Riedl

2700
Citations
An algorithmic framework for performing collaborative filtering

Unknown

2556
Citations
Explaining collaborative filtering recommendations

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

2482
Citations
Application of Dimensionality Reduction in Recommender System - A Case Study

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

2176
Citations
Collaborative Filtering Recommender Systems

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

1546
Citations
Being accurate is not enough: how accuracy metrics have hurt recommender systems

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

1464
Citations
Combining collaborative filtering with personal agents for better recommendations

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

1351
Citations
Recommender systems: from algorithms to user experience

Joseph A. Konstan;John Riedl

1009
Citations
An Empirical Analysis of Design Choices in Neighborhood-Based Collaborative Filtering Algorithms

Jon Herlocker;Joseph A. Konstan;John Riedl

981
Citations
Building Successful Online Communities: Evidence-Based Social Design

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

948
Citations
Shilling recommender systems for fun and profit

Shyong K. Lam;John Riedl

889
Citations
Getting to know you: learning new user preferences in recommender systems

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

838
Citations
MovieLens unplugged: experiences with an occasionally connected recommender system

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

829
Citations
Is seeing believing?: how recommender system interfaces affect users' opinions

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

773
Citations

Frequent Co-Authors

Joseph A. Konstan University of Minnesota

Bharat Bhargava Purdue University West Lafayette

Loren Terveen University of Minnesota

Ed H. Chi Google (United States)

George Karypis University of Minnesota

Dan Cosley National Science Foundation

Mark Claypool Worcester Polytechnic Institute

Robert E. Kraut Carnegie Mellon University

Gloria Mark University of California, Irvine

Sara Kiesler Carnegie Mellon University

External Links

Wikipedia of John Riedl Personal website of John Riedl

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