关键词: 海量评价数据, 用户偏好, D-S证据理论, 证据融合, MapReduce

Abstract: User rating on products or information services includes reviews and scores, and reflects user behavior      information, such as interest, opinions and preferences. In order to represent the degrees of user preferences on products inherently and quantitatively, starting from the massive rating data, this paper defines user preference based on the idea of marginal utility. Then, this paper describes the uncertainties of relevant influence factors on user preferences and the mutual relationships among these factors based on the D-S evidence theory. Taking the vocabulary in a review, the vocabulary including positive/negative words and the score as the evidence of user preference respectively, this paper gives the operator for combining the relevant factors jointly, as well as the computation method and mechanism for discovering user preferences based on MapReduce. The experimental results on correctness, execution time, speedup and parallel efficiency verify the effectiveness of the method proposed in this paper.

Key words: massive rating data, user preference, D-S evidence theory, evidence fusion, MapReduce