The DOI matches its Crossref record.
An Algorithmic Framework for Performing Collaborative Filtering
Abstract
column Share on An Algorithmic Framework for Performing Collaborative Filtering Authors: Jonathan L. Herlocker University of Minnesota University of MinnesotaView Profile , Joseph A. Konstan University of Minnesota University of MinnesotaView Profile , Al Borchers University of Minnesota University of MinnesotaView Profile , John Riedl University of Minnesota University of MinnesotaView Profile Authors Info & Claims ACM SIGIR ForumVolume 51Issue 2July 2017 pp 227–234https://doi.org/10.1145/3130348.3130372Published:02 August 2017Publication History 63citation823DownloadsMetricsTotal Citations63Total Downloads823Last 12 Months45Last 6 weeks3 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 24
- ACM. Special issue on information filtering. Gommunciations of the ACM, 35(12) , December 1992 . ACM. Special issue on information filtering. Gommunciations of the ACM, 35(12), December 1992.
- 10.1145/245108.245124 · DOI · Paper page
- Chumki Basu , Haym Hirsh , and William Cohen . Recommendation as classification: using social and content-based information in recommendation . In Proceedings of the 1998 Workshop on Recommender Systems , pages 11 - 15 . AAAI Press , August 1998 . Chumki Basu, Haym Hirsh, and William Cohen. Recommendation as classification: using social and content-based information in recommendation. In Proceedings of the 1998 Workshop on Recommender Systems, pages 11-15. AAAI Press, August 1998.
- Daniel Billsus and Michael J. Pazzani . Learning collaborative information filters . In Proceedings of the 1998 Workshop on Recommender Systems. AAAI Press , August 1998 . Daniel Billsus and Michael J. Pazzani. Learning collaborative information filters. In Proceedings of the 1998 Workshop on Recommender Systems. AAAI Press, August 1998.
- John S. Breese , David Heckerman , and Carl Kadie . Empirical analysis of predictive algorithms for collaborative filtering . In Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence (UAI-98) , pages 4352 , San Francisco , July 24-26 1998 . John S. Breese, David Heckerman, and Carl Kadie. Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence (UAI-98), pages 4352, San Francisco, July 24-26 1998.
- 10.1002/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9 · DOI
- 10.1145/138859.138867 · DOI · Paper page
- 10.1145/223904.223929 · DOI · Paper page
- 10.1145/245108.245123 · DOI · Paper page
- 10.1145/245108.245126 · DOI · Paper page
- 10.1145/176789.176792 · DOI · Paper page
- 10.1145/223904.223930 · DOI
- James T. McClave and Frank H . Dietrich II. Statistics . Dellen Publishing Company , 1988 . James T. McClave and Frank H. Dietrich II. Statistics. Dellen Publishing Company, 1988.
- 10.5555/188490.188583 · doi:10.5555/188490.188583
- 10.5555/6771 · doi:10.5555/6771
- 10.1145/192844.192905 · DOI · Paper page
- 10.1207/s15516709cog0304_3 · DOI · Paper page
- 10.1016/0306-4573(88)90021-0 · DOI · Paper page
- 10.1145/289444.289509 · DOI · Paper page
- 10.1145/223904.223931 · DOI · Paper page
- 10.1126/science.3287615 · DOI · Paper page
- 10.1145/245108.245122 · DOI · Paper page
- C. J. van Rijsbergen . Information Retrieval , chapter 7. Butterworths , 1979 . C. J. van Rijsbergen. Information Retrieval, chapter 7. Butterworths, 1979.
- 10.5555/857186.857579 · doi:10.5555/857186.857579
Cited by
Item-based collaborative filtering recommendation algorithms
Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2001) · Proceedings of the 10th international conference on World Wide Web · doi:10.1145/371920.372071 · Cited by 9,135
Self-citationEvaluating collaborative filtering recommender systems
Herlocker, J. L., Konstan, J. A., Terveen, L. G., & Riedl, J. T. (2004) · ACM Transactions on Information Systems · doi:10.1145/963770.963772 · Cited by 5,798
Self-citationExplaining collaborative filtering recommendations
Herlocker, J. L., Konstan, J. A., & Riedl, J. (2000) · Proceedings of the 2000 ACM conference on Computer supported cooperative work · doi:10.1145/358916.358995 · Cited by 1,731
Self-citationLessons from the Netflix prize challenge
Bell, R. M., & Koren, Y. (2007) · ACM SIGKDD Explorations Newsletter · doi:10.1145/1345448.1345465 · Cited by 727
E-Learning personalization based on hybrid recommendation strategy and learning style identification
Klašnja-Milićević, A., Vesin, B., Ivanović, M., & Budimac, Z. (2011) · Computers & Education · doi:10.1016/j.compedu.2010.11.001 · Cited by 580
Metadata
- Authors
- Herlocker, J. L., Konstan, J. A., Borchers, A., & Riedl, J.
- Venue
- ACM SIGIR Forum
- Published
- 2017-08-02
- Volume
- 51
- Issue
- 2
- Pages
- 227-234
- ISSN
- 0163-5840 (ISSN-L)
- OpenAlex
- W2085937320
- Cited by
- 2,512
- References
- 0
- FWCI
- 219.05
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: An Algorithmic Framework for Performing Collaborative Filtering. https://app.cochat.ai/papers/10.1145/3130348.3130372
- The paper
- Herlocker, J. L., Konstan, J. A., Borchers, A., & Riedl, J. (2017). An Algorithmic Framework for Performing Collaborative Filtering. ACM SIGIR Forum. https://doi.org/10.1145/3130348.3130372
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
