ACM SIGIR Forum· 2017
An Algorithmic Framework for Performing Collaborative Filtering
- 2,555citations
- 2017year
Short summary
This paper introduces a novel algorithmic framework for collaborative filtering, a technique used in recommendation systems.
AI-generated from the title and abstract; the full text is not read.
Key points
- Introduces a new algorithmic framework for collaborative filtering.
- Focuses on improving recommendation system performance.
- Provides a structured approach for implementation.
AI-generated from the title and abstract; the full text is not read.
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
The authors' abstract, as published at the source. ACM SIGIR Forum, 2017 · DOI ↗
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Field: Computer Science Applications
Computer Science ApplicationsComputer Science