John Riedl

157 papers receiving 27.6k citations

John Riedl's Hit Papers

An Algorithmic Framework for Performing Collaborative Filtering 2017 · 371 citations
3710+10+21Years since publication10002.0k3.0k4.0k5.0k

Peers

John Riedl
Comparison fields: 5 of 167
  • Information Systems 22.7k
  • Computer Science Applications 2.7k
  • Computer Vision and Pattern Recognition 7.0k
  • Management Science and Operations Research 4.1k
  • Artificial Intelligence 10.3k
Replace Joseph A. Konstan with:
Joseph A. Konstan United States
Jon Kleinberg United States
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John Riedl relative to Joseph A. Konstan United States Joseph A. Konstan's profile →
Citations per field
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Citations per year

Countries citing papers authored by John Riedl

Since Specialization
Citations

This map shows the geographic impact of John Riedl's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by John Riedl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Riedl more than expected).

Fields of papers citing papers by John Riedl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John Riedl. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by John Riedl. The network helps show where John Riedl may publish in the future.

Co-authors

The 25 scholars most cited alongside John Riedl, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with John Riedl Line = papers co-authored together John Riedl links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 161 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Item-based collaborative filtering recommendation algorithms
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20015757
2
Evaluating collaborative filtering recommender systems
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20043721
3
GroupLens
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19943250
4
GroupLens
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19971544
5
An algorithmic framework for performing collaborative filtering
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19991282
6
Analysis of recommendation algorithms for e-commerce
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20001142
7
Explaining collaborative filtering recommendations
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20001084
8
Recommender systems in e-commerce
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19991015
9
E-Commerce Recommendation Applications
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2001978
10
Being accurate is not enough
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2006647
11
Building Successful Online Communities: Evidence-Based Social Design
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2012459
12
Recommender systems: from algorithms to user experience
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2012455
13
An Empirical Analysis of Design Choices in Neighborhood-Based Collaborative Filtering Algorithms
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2002433
14
Combining collaborative filtering with personal agents for better recommendations
1999428
15 2004417
16
An Algorithmic Framework for Performing Collaborative Filtering
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2017371
17 2003348
18 2002340
19 2003296
20 2002286

About John Riedl

John Riedl is a scholar working on Information Systems, Artificial Intelligence, Computer Networks and Communications, Communication and Management Science and Operations Research, having authored 161 papers that have together received 30.1k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (59 papers), Wikis in Education and Collaboration (27 papers), Advanced Bandit Algorithms Research (20 papers), Open Source Software Innovations (19 papers), Distributed systems and fault tolerance (17 papers), Video Analysis and Summarization (11 papers), Knowledge Management and Sharing (10 papers) and Peer-to-Peer Network Technologies (9 papers). The work is most often cited by research in Information Systems (22.7k citations), Computer Science Applications (2.7k citations), Computer Vision and Pattern Recognition (7.0k citations), Management Science and Operations Research (4.1k citations) and Artificial Intelligence (10.3k citations). John Riedl has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Joseph A. Konstan, Jonathan L. Herlocker, Badrul Sarwar, George Karypis, Loren Terveen, J. Ben Schafer, Paul Resnick, Peter Bergström, Shyong K. Lam and Al Borchers. Their work appears in journals such as Computer, ACM Transactions on Information Systems, Communications of the ACM, IEEE Transactions on Knowledge and Data Engineering and ACM Transactions on Interactive Intelligent Systems.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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