迅速增长的移动网络服务给人们带来沉重的移动信息负担.移动用户偏好提取方法是缓解"移动信息过载"问题的有效手段.受加工水平模型和分布式认知理论的启发,提出一种基于认知心理学的移动用户偏好提取方法.在移动用户偏好信息结构建模的基础上,引入服务加工水平认知、有效上下文认知的概念,并计算其对用户偏好提取的影响,然后分别提取基于服务加工水平认知和基于有效上下文认知的用户偏好,最终提取综合的用户偏好.实验结果表明,该方法能有效提高移动用户偏好提取精确度,为用户提供满足个性化需求的移动网络服务.

The rapid growth of the number of mobile services provides enormous potential for mobile users in different contexts to find mobile information of interest.Mobile user preferences elicitation has been used as a valid means to ease the "mobile information overload" problem.Inspired by the model of level of processing and the theory of distributed cognition,a cognitive psychology-based approach to user preferences elicitation for mobile network services is proposed.It uses a six-tuple to describe the data structure of user preferences information,analyzes the level of processing of services for users to elicit context-free user preferences,then identifies valid types of contexts as well as their influences on user preferences,and finally elicits converged user preferences.Experimental comparisons of this approach against some baseline methods with a synthetic data set have been conducted,showing improvements in performance.