Faculty Publications
View Through Metalens: Usage Patterns For A Meta-Recommendation System
Document Type
Article
Journal/Book/Conference Title
IEE Proceedings: Software
Volume
151
Issue
6
First Page
267
Last Page
279
Abstract
In a world where a person's number of choices can be overwhelming, recommender systems help users find and evaluate items of interest. They do so by connecting users with information regarding the content of recommended items or the opinions of other individuals. Such systems have become powerful tools in domains such as electronic commerce, digital libraries and knowledge management. The authors address such systems, as well as a relatively new class of recommender system called meta-recommenders. Meta-recommenders provide users with personalised control over the generation of a single recommendation list formed from a combination of rich data using multiple information sources and recommendation techniques. They discuss observations made from the public trial of a meta-recommender system in the domain of movies and lessons learned from the incorporation of features that allow persistent personalisation of the system. Finally, they consider the challenges of building real-world, usable meta-recommenders across a variety of domains. © IEE, 2004.
Department
Department of Computer Science
Original Publication Date
11-1-2004
DOI of published version
10.1049/ip-sen:20041166
Recommended Citation
Schafer, J. B.; Konstan, J. A.; and Riedl, J., "View Through Metalens: Usage Patterns For A Meta-Recommendation System" (2004). Faculty Publications. 3071.
https://scholarworks.uni.edu/facpub/3071