The Effect of Diversity Implementation on Precision in Multicriteria Collaborative Filtering

Abstract

—This research was triggered by the criticism on the emergence of homogeneity in recommendation within the collaborative filtering based recommender systems that put similarity as the main principle in the algorithm. To overcome the problem of homogeneity, this study proposes a novelty, i.e. the diversity of recommendations applied to the multicriteria collaborative filtering-based document recommender systems. Development of the diversity recommendation was made by the two techniques, the first is to compare the similarity of content and the second is to use a variation of the criteria. The application of diversity, both content and criteria-based, was proven to provide a sufficiently significant influence on the increase of recommendation precision.