An efficient mechanism for compensating vague pattern identification in support of a multi-criteria recommendation system

A vague pattern usually makes the result of pattern identification specious. Most existing identification algorithms try to upgrade their identification accuracies by improving the clearness of the vague pattern. However, this improvement can be limited due to the poor quality of the pattern itself. Hence, the identification result can still be untrustworthy and thus a user needs to repeat the algorithm to find another possible answer, which can be quite time-consuming. In this paper, we propose a novel pattern recommendation mechanism which is able to obtain multiple highly possible answers from a large datapool based on a given vague pattern. By using the identification algorithm only one time, a user can select a correct identification answer from these candidates given by the recommendation system. Three strategies are proposed in this paper. Experiments are performed to demonstrate the effectiveness and efficiency of the proposed mechanism.