A fuzzy hybrid recommender system

Recommender Systems (RSs) are largely used nowadays to generate interest items or products for web users. This paper proposed a novel recommendation technique based on fuzzy logic that combines a collaborative filtering and taxonomic based filtering together to make better quality recommendations as well as alleviate Stability/ Plasticity problem in RSs. Empirical evaluations are conducted, results are promising and they shown that the proposed technique is feasible and effective.