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Evidence-Based Behavioral Model for Calendar Schedules of Individual Mobile Phone Users

机译:个人手机用户日历计划的基于证据的行为模型

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The electronic calendar usually serves as a personal organizer and is a valuable resource for managing daily activities or schedules of the users. Naturally, a calendar provides various contextual information about individual's scheduled events/appointments, e.g., meeting. A number of researchers have utilized such information to predict human behavior for mobile communication, by assuming a predefined event-behavior mapping which is static and non-personalized. However, in the real world, people differ from each other in how they respond to incoming calls during their scheduled events, even a particular individual may respond differently subject to what type of event is scheduled in the calendar. Thus a static behavioral model does not necessarily map to calendar schedules and corresponding phone call response behavior of individuals. Therefore, we propose an evidencebased behavioral model (EBM) that dynamically identifies the actual call response behavior of individuals for various calendar events based on their mobile phone log that records the data related to a user's phone call activities. Experiments on real datasets show that our proposed technique better captures the user's call response behavior for various calendar events, thereby enabling more appropriate rules to be created for the purpose of automated handling of incoming calls in an intelligent call interruption management system.
机译:电子日历通常用作个人组织者,并且是用于管理用户的日常活动或时间表的宝贵资源。自然地,日历提供关于个人的预定事件/约会例如会议的各种上下文信息。通过假设静态和非个性化的预定义事件-行为映射,许多研究人员已利用此类信息来预测移动通信的人类行为。但是,在现实世界中,人们在计划的事件中如何响应传入呼叫彼此之间是不同的,即使特定的个人也可能会根据日历中计划的事件类型做出不同的响应。因此,静态行为模型不一定映射到个人的日程表和相应的电话响应行为。因此,我们提出了一个基于证据的行为模型(EBM),该模型基于记录了与用户电话活动相关的数据的他们的移动电话日志,动态地识别个人对于各种日历事件的实际呼叫响应行为。在真实数据集上进行的实验表明,我们提出的技术可以更好地捕获各种日历事件的用户呼叫响应行为,从而可以创建更合适的规则,以在智能呼叫中断管理系统中自动处理传入的呼叫。

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