一种用户态活动感知计算模型的设计与实现

A activity-based computing Model Design and Implementation

活动感知计算通过提取分析出用户某种状态的复合信息减少用户交互,更好的无缝融合用户当前的上下文信息和周围的情景,从而逐渐成为上下文感知计算中一个新的研究热点。本文提出了一种能较为准确表达用户当前整体状态的复合信息概念——用户态,和一套感知、分析、推理其的系统模型。根据模型过滤后的个性化推荐服务内容更加准确,服务质量和使用效率得到进一步提高。

The Activity Based Computing minimizes user interaction with the method of extracting and analyzing the users＇ composite information about some state.And it can integrate the users＇ current context information and the environment around seamlessly.So the activity based computing has gradually become a new research hotspot of Context-aware Computing.In this paper,we propose a composite information concept that can express the users＇current overall state more precisely-User Status and built systematic model that can analyze and deduct it. Through the experiments,we find that after the model＇s filtration,the contents of the personalized recommendation service become more precise,and both the service quality and efficiency are improved.