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One of the most used approaches for providing recommendations in variousonline environments such as e-commerce is collaborative filtering. Although,this is a simple method for recommending items or services, accuracy andquality problems still exist. Thus, we propose a dynamic multi-levelcollaborative filtering method that improves the quality of therecommendations. The proposed method is based on positive and negativeadjustments and can be used in different domains that utilize collaborativefiltering to increase the quality of the user experience. Furthermore, theeffectiveness of the proposed method is shown by providing an extensiveexperimental evaluation based on three real datasets and by comparisons toalternative methods.

A dynamic multi-level collaborative filtering method for improved recommendations