A Cognitive Psychology-Based Approach to User Preferences Elicitation for Mobile Network Services

WANG Li-cai; MENG Xiang-wu; ZHANG Yu-jie

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A Cognitive Psychology-Based Approach to User Preferences Elicitation for Mobile Network Services

更新时间：2025-07-16

- A Cognitive Psychology-Based Approach to User Preferences Elicitation for Mobile Network Services
- Acta Electronica Sinica Vol. 39, Issue 11, Pages: 2547-2553(2011)
- 作者机构：
  
  1. 北京邮电大学计算机学院,北京,100876
  2. 北京邮电大学智能通信软件与多媒体北京市重点实验室,北京,100876
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP301
- Published：2011
- 稿件说明：
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WANG Li-cai, MENG Xiang-wu, ZHANG Yu-jie. A Cognitive Psychology-Based Approach to User Preferences Elicitation for Mobile Network Services[J]. Acta Electronica Sinica, 2011, 39(11): 2547-2553.
DOI：

WANG Li-cai, MENG Xiang-wu, ZHANG Yu-jie. A Cognitive Psychology-Based Approach to User Preferences Elicitation for Mobile Network Services[J]. Acta Electronica Sinica, 2011, 39(11): 2547-2553. DOI：

摘要

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.

Abstract

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.

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