Collaborative Filtering Recommender Systems
Abstract
Recommender systems are an important part of the information and e-commerce ecosystem. They represent a powerful method for enabling users to filter through large information and product spaces. Nearly two decades of research on collaborative filtering have led to a varied set of algorithms and a rich collection of tools for evaluating their performance. Research in the field is moving in the direction of a richer understanding of how recommender technology may be embedded in specific domains. The differing personalities exhibited by different recommender algorithms show that recommendation is not a one-size-fits-all problem. Specific tasks, information needs, and item domains represent unique problems for…
Citation impact
- FWCI
- 62.65
- Percentile
- 100%
- References
- 151
Authors
3- MDMichael D. EkstrandCorresponding
University of Minnesota
- JTJohn T. Riedl
University of Minnesota
- JAJoseph A. Konstan
University of Minnesota
Topics & keywords
- Recommender system
- Collaborative filtering
- Computer science
- Information retrieval
- World Wide Web