Ontological modeling of motivational messages for physical activity coaching

Claudia Villalonga, H. O. D. Akker, H. Hermens, L. Herrera, H. Pomares, I. Rojas, O. Valenzuela, O. Baños
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引用次数: 12

Abstract

Smart coaching systems are named to play a central role in both prevention and intervention strategies for behavioral change. While relevant progresses have been made in terms of automatic and continuous monitoring of behavioral aspects, e.g. amount and variety of physical activity, coaching and feedback techniques are still in an infancy stage. Current smart coaching strategies are mostly based on handcrafted messages which hardly personalize to the needs, context and preferences of each user. In order to make these recommendations more realistic, engaging and effective more flexible and sophisticated strategies are needed. This paper presents an ontology-based approach to model personalizable motivational messages for promoting healthy physical activity. The proposed ontology not only models the message intention and its components, e.g. argument, feedback or followup, but also its content, i.e. action, place, time or object required to perform the recommended activity. Through this ontology the messages can also be categorized into multiple classes, e.g. sedentary, mild or vigorous activities, and retrieved based on the preferences, needs and context of the user. Additional information not explicitly present on the messages can be inferred from the ontology by applying reasoning techniques and used to enhance the message retrieval process.
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体育训练动机信息的本体建模
智能教练系统被命名为在行为改变的预防和干预策略中发挥核心作用。虽然在自动和持续监测行为方面取得了相关进展,例如体育活动的数量和种类,但指导和反馈技术仍处于起步阶段。目前的智能教练策略大多是基于手工制作的信息,几乎没有个性化的需求,背景和每个用户的偏好。为了使这些建议更现实、更有吸引力和更有效,需要更灵活和复杂的战略。本文提出了一种基于本体的方法来建模个性化的激励信息,以促进健康的身体活动。提出的本体不仅对消息意图及其组成部分(如争论、反馈或后续行动)建模,还对其内容(如执行推荐活动所需的动作、地点、时间或对象)建模。通过这个本体,消息也可以被分类为多个类别,例如久坐、轻度或剧烈的活动,并根据用户的偏好、需求和上下文进行检索。可以通过应用推理技术从本体中推断出未显式呈现在消息上的其他信息,并用于增强消息检索过程。
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