应用机器学习技术提高用户对泛在服务的接受度
Applying machine learning techniques to improve user acceptance on ubiquitous environement
摘要：
泛在信息访问在当今社会变得越来越重要，研究的目的是使其适应用户。我们的工作包括在应用机器学习技术，以适应信息访问时，系统只知道用户的社会群体，而不知道任何关于用户的兴趣无处不在的系统提供给用户。适配过程将动作与用户的感知情况相关联。关联是基于用户对系统行为的反馈。我们的方法带来了一些问题的解决方案，当应用机器学习技术的系统，在系统和用户之间的交互开始时，用户对系统的接受。
英文摘要：
Ubiquitous information access becomes more and more important nowadays and research is aimed at making it adapted to users. Our work consists in applying machine learning techniques in order to adapt the information access provided by ubiquitous systems to users when the system only knows the user social group, without knowing anything about the user interest. The adaptation procedures associate actions to perceived situations of the user. Associations are based on feedback given by the user as a reaction to the behavior of the system. Our method brings a solution to some of the problems concerning the acceptance of the system by users when applying machine learning techniques to systems at the beginning of the interaction between the system and the user.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
