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Personalized Information Gathering Using Implicit User Feedback in a Multiple Personal Device Environment

机译:在多个个人设备环境中使用隐式用户反馈进行个性化信息收集

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We propose a personalized information gathering system PerIGS that exploits implicit user feedback in a multiple personal device environment. PerIGS extracts imposing words that induce user's choice from recommended news articles, and constructs user preference profile based on observed user behaviors. A user profile is shared by multiple personal devices, and PerIGS gathers, filters, and recommends news articles according to this shared profile. We organize the user profile in a hierarchical category structure to deal with the uncertainty of user interests. This structure also enables the system to track and recognize the changes of user interests for each domain more effectively. The results of a series of experiments measuring user satisfaction for recommended news articles indicated that PerIGS can effectively utilize user profiles for news filtering and recommendation.
机译:我们提出了一种个性化的信息收集系统PerIGS,该系统利用了多个个人设备环境中的隐式用户反馈。 PerIGS从推荐的新闻文章中提取诱导用户选择的强加词,并根据观察到的用户行为构建用户偏好配置文件。一个用户配置文件由多个个人设备共享,PerIGS根据此共享的配置文件收集,过滤和推荐新闻文章。我们以分级类别结构组织用户个人资料,以应对用户兴趣的不确定性。这种结构还使系统能够更有效地跟踪和识别每个域的用户兴趣的变化。一系列测量用户对推荐新闻的满意度的实验结果表明,PerIGS可以有效地利用用户配置文件进行新闻过滤和推荐。

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