Establishing Grey Criteria Similarity Measures for Multi-criteria Recommender Systems

Recommendation methods are becoming more and more important for the online shopping websites. The development of multi-criteria recommender systems such as initiator recommendation according to customers' preferences have been a noteworthy decision problem. Also, it is interesting to study how to design initiator recommender systems for group-buying. Whereas grey relational analysis (GRA) is a useful technique that can assess the relationships among patterns, this study presents an aggregation-function-based method by using the proposed grey criterion similarity. The proposed similarity measure reveals that the greater the strength of the relationship of one user with another one for a criterion, the greater criterion similarity of the former to the latter Besides, the aggregation-function-based method can be used to predict unknown overall ratings by using the proposed criterion similarity to estimate multi-criteria ratings. Experimental results on a group-buying website have demonstrated that the generalization ability of the aggregation function-based method using the proposed grey criterion similarity performs well in comparison to that using other criterion similarities.