On a Hybrid Rule Based Recommender System

Authors:
FENG ZHANG;HUI-YOU CHANG
Affiliations:
Sun Yat-sen University;Sun Yat-sen University
Venue:
CIT '05 Proceedings of the The Fifth International Conference on Computer and Information Technology
Year:
2005

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Abstract

Compared with relative recently-reported conterparts, a novel recommender system prototype is implemented. Its efforts focus on the three essential issues as a whole that recommender systems have to handle: data source, data modeling and recommendation strategy. It is based on a common data format and introduces a hybrid-rule model with a strategy of one-round table scanning. Laboratory experiment results show that this recommender system produces a better outcome.