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Submission declined on 22 November 2024 by SafariScribe (talk).
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This draft has been resubmitted and is currently awaiting re-review. |  |
| Developer(s) | GroupLens Research, Michael D. Ekstrand |
|---|---|
| Initial release | October 23, 2010 |
| Stable release | 0.14.4
/ 2024 |
| Written in | Python, formerly Java |
| Operating system | Cross-platform |
| Platform | Linux, macOS, Windows |
| Type | Recommender system, Software library |
| License | MIT License |
| Website | lenskit.org |
LensKit is an open-source toolkit for developing and researching recommender systems. Originally released in 2010/11[1][2] as a Java-based framework, it was later re-implemented in Python as LensKit for Python (LKPY)[3]. It is considered "mature" and "well documented".[4] Along with a few other libraries, LensKit was one of the first recommender-system software libraries for "rapid prototyping" due to an "easy-to-use" model execution[5][6]. The Recommender-Systems.com Blog recommends LensKit for developers and researchers who are new to the field[7] and considers it "one of the best choices".[8] The well regarded "List of Recommender Systems" with 4.6k stars on GitHub lists LensKit as #1 in the list of academic recommender systems.[9]
- ^ Ekstrand, Michael D.; Ludwig, Michael; Kolb, Jack; Riedl, John T. (2011). "LensKit: A Modular Recommender Framework". Proceedings of the Fifth ACM Conference on Recommender Systems (RecSys '11). ACM. p. 349. doi:10.1145/2043932.2044001.
- ^ Ekstrand, Michael D.; Ludwig, Michael; Konstan, Joseph A.; Riedl, John T. (2011-10-23). "Rethinking the recommender research ecosystem: Reproducibility, openness, and LensKit". Proceedings of the fifth ACM conference on Recommender systems. ACM. pp. 133–140. doi:10.1145/2043932.2043958. ISBN 978-1-4503-0683-6.
- ^ Ekstrand, Michael D. (2020). "LensKit for Python: Next-Generation Software for Recommender Systems Experiments". Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM '20). ACM. pp. 2999–3007. doi:10.1145/3340531.3412778.
- ^ Chulyadyo, Rajani; Leray, Philippe (2017-12). A Framework for Offline Evaluation of Recommender Systems based on Probabilistic Relational Models (Report). Laboratoire des Sciences du Numérique de Nantes ; Capacités SAS.
{{cite report}}: Check date values in:|date=(help) - ^ "Towards Responsible AI in Recommender Systems". tesidottorato.depositolegale.it. Retrieved 2024-11-22.
- ^ Mohammadi, Amir Reza; Karimi, Amir-Hossein; Bohlouli, Mahdi; Zangerle, Eva; Specht, G¨unther (2023). "HPT4Rec: AutoML-based Hyperparameter Self-Tuning Framework for Session-based Recommender Systems". S2CID 270879801.
{{cite journal}}: Cite journal requires|journal=(help) - ^ "Recommender-System Software Libraries & APIs – RS_c". Retrieved 2024-11-22.
- ^ "Creating a Recommender System Prototype Using LensKit and MovieLens – RS_c". Retrieved 2024-11-22.
- ^ Jenson, Graham (2024-11-21), grahamjenson/list_of_recommender_systems, retrieved 2024-11-22
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