INTEGRATING INTERACTION AND SIMILARITY THRESHOLD OF USER’S INTERESTS FOR TOPIC TRUST COMPUTATION

Abstract

This paper proposes a computational model of topic trust being constructed from users similarity and levels of their interaction. It is defined as function of  imilarity degrees in interests and levels of interaction in topics among users. Based on this model, we may estimate trustworthy values among peers in all cases with some direct and indirect interaction or without any interaction. The proposed approach may overcome limitation in the high computational cost of ropagation methods based on graph models.