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Providing Relevant Background Information in Smart Environments

机译:在智能环境中提供相关背景信息

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摘要

In this paper we describe a system, called GAIN (Group Adapted Interaction for News), which selects background information to be displayed in public shared environments according to preferences of the group of people present in there. In ambient intelligence contexts, we cannot assume that the system will be able to know every users physically present in the environment and therefore to access to their profiles in order to compute the preferences of the entire group. For this reason, we assume that group members may be i) totally unknown, ii) completely or iii) partially known by the system. As we describe in the paper, in the first case, the system uses a group profile that is built statistically according to the results of a preliminary study. In the second case, the model of the group is created from the profiles of known users. In the third situation the group interests are modeled by integrating preferences of known members with a statistical prediction of the interests of unknown ones. Evaluation results proved that adapting news display to the group was more effective in matching the members' interests in all the three cases than the in the non-adaptive modality.
机译:在本文中,我们描述了一个名为GAIN(新闻的组适应交互)的系统,该系统根据在场共享人群的偏好选择要在公共共享环境中显示的背景信息。在环境情报环境中,我们不能假设系统将能够知道环境中实际存在的每个用户,因此可以访问他们的配置文件以计算整个组的偏好。因此,我们假定组成员可能是:i)系统完全未知,ii)完全未知或iii)部分已知。正如我们在论文中所描述的,在第一种情况下,系统使用根据初步研究结果统计构建的组概要文件。在第二种情况下,从已知用户的配置文件创建组的模型。在第三种情况下,通过将已知成员的偏好与未知成员的利益的统计预测相结合来模拟群体利益。评估结果证明,在这三种情况下,使新闻显示适应组更有效地匹配了成员的兴趣,而不是非适应性方式。

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