weHelp: A Reference Architecture for Social Recommender Systems
Swapneel Kalpesh Sheth; Nipun Arora; Christian Murphy; Gail E. Kaiser
- weHelp: A Reference Architecture for Social Recommender Systems
Sheth, Swapneel Kalpesh
Kaiser, Gail E.
- Technical reports
- Computer Science
- Permanent URL:
- Columbia University Computer Science Technical Reports
- Part Number:
- Department of Computer Science, Columbia University
- Publisher Location:
- New York
- Recommender systems have become increasingly popular. Most of the research on recommender systems has focused on recommendation algorithms. There has been relatively little research, however, in the area of generalized system architectures for recommendation systems. In this paper, we introduce weHelp: a reference architecture for social recommender systems — systems where recommendations are derived automatically from the aggregate of logged activities conducted by the system's users. Our architecture is designed to be application and domain agnostic. We feel that a good reference architecture will make designing a recommendation system easier; in particular, weHelp aims to provide a practical design template to help developers design their own well-modularized systems.
- Computer science
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