Evidence Combination Focusing on Significant Focal Elements for Recommender Systems

Abstract

In this paper, we develop a solution for evidence combination, called 2-probabilities focused combination, that concentrates on significant focal elements only. Firstly, in the focal set of each mass function, elements with their probabilities in top two highest probabilities are retained; others are considered as noise, which have been generated when assigning probabilities to the mass function and/or by related evidence combination tasks had already been done before, and eliminated. The probabilities of eliminated elements are added to the probability of the whole set element. The achieved mass functions are called 2-probabilities focused mass functions. Secondly, Dempster’s rule of combination is used to combine pieces of evidence represented as 2-probabilities focused mass functions. Finally, the combination result is transformed into the corresponding 2-probabilities focused mass function. Actually, the proposed solution can be employed as a useful tool for fusing pieces of evidence in recommender systems using soft ratings based on Dempster-Shafer theory; thus, we also present a way to integrate the proposed solution into these systems. Besides, the experimental results show that the performance of the proposed solution is more effective than a typically alternative solution called 2-points focused combination solution.

This research work was supported by JSPS KAKENHI Grant No. 25240049.