OpenAlex
PricingAboutJobs
Log inGet started
Work

Recommender systems: from algorithms to user experience

HTML PDF

Year: 2012
Type: article
Source: User Modeling and User-Adapted Interaction
DOI: 10.1007/s11257-011-9112-x
Authors: Joseph A. Konstan, John Riedl
Institution: University of Minnesota
Language: English

Topic: Recommender Systems and Techniques
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences

Open Access status: bronze

Funder: National Science Foundation
Awards: CAREER: Algorithmic Issues in Collaborative Filtering, Enhanced Digital Libraries Through Recommendation: Exploring the Use of Citations, Personal Bibliographies, and Metadata to Synthesize Library Services for Individuals, HCC: Medium: Collaborative Research: Guiding Folksonomy Development to Enable Novel Tagging Applications, ITR: Collaborative Research: Designing On-Line Communities to Enhance Participation -- Bridging Theory and Practice, Helping Hands: Computer Support for Community-Maintained Artifacts of Lasting Value, GroupLens: Scalable Collaborative Filtering for the Internet, Reading a Balanced Diet: Foraging in Information Communities, Reflective GroupLens: Collaborative Filtering in Self-Aware Communities, HCC-Large: Collaborative Research: Understanding Online Volunteer Communities: Toward Theory-Based Design
OpenAlex ID: W2112856797
FWCI: 80.92
Cites: 96
Cited by: 817
Related to: 10
OpenAlex
Nonprofit
Open DataOpen Data
Open Source
Product
Search
Compare
Pricing
Repositories
Unpaywall
Unsub
Developers
API docs
Data snapshot
Status
Source code
Organization
About
Team
Testimonials
Brand
Jobs
Community
Help center
Contact
Events
Blog
Mailing list
Supporters
Legal
Privacy
Accessibility
Terms