On a Hybrid Rule Based Recommender System
Feng Zhang, Hui-You Chang · 2005
Compared with relative recently-reported counterparts, 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