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Efficient profiling and distributed synchronization of statistical user models for content-targeting and real-time applications

机译:针对内容定位和实时应用的统计用户模型的有效配置和分布式同步

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This work presents an efficient approach for managing distributed user profiles in the use-case of the semi-autonomous or fully autonomous connected car. A user profile is a collection about user's personal preferences and statistical data on user's previous interactions with all compatible connected systems outside and inside the car. Managing the user profile practically means dynamically updating the profile based on the interaction with the vehicle's human-machine interfaces and using it to answer complex queries placed by the vehicle's applications. The queries can range between user interface personalization queries (what is the user's favorite radio station), over product-placement related queries (are we going to pass next to a restaurant the user might be interested in) to safety-relevant queries (is the senior driver paying adequate attention to the direction of a detected obstacle). The focus is placed on reducing the computational complexity of user profiling and synchronization of distributed user profiles.
机译:这项工作提出了一种在半自动或全自动驾驶汽车的用例中管理分布式用户配置文件的有效方法。用户个人资料是有关用户个人喜好和用户先前与车内外所有兼容连接系统交互的统计数据的集合。管理用户配置文件实际上意味着基于与车辆人机界面的交互来动态更新配置文件,并使用它来回答车辆应用程序提出的复杂查询。这些查询的范围介于用户界面个性化查询(用户最喜欢的广播电台),产品放置相关的查询(我们将传递给用户可能感兴趣的饭店旁边)还是与安全相关的查询(是否是高级驾驶员要充分注意发现的障碍物的方向)。重点放在降低用户配置文件的计算复杂性和分布式用户配置文件的同步上。

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