体育运动电子教练个性化建议(ontorecommodel):卡塔尔世界杯8强波胆分析本体建模%A Chatterjee,Ayan %A Prinz,Andreas %+ Agder大学电子健康中心信息与通信技术系，Jon Lilletuns Vei 9，挪威格里姆斯塔德，4879,47 94719372,ayan.chatterjee@uia.no %K描述逻辑%K本体%K e-coach %K推理%K推荐生成%D 2022 %7 23.6.2022 %9原文%J JMIR Med Inform %G English %X自动电子指导可以通过早期健康风险预测、个性化建议生成和目标评估来激励个人过上健康的生活方式。多项研究报告了不间断和自动监测行为方面(如久坐时间、运动量和身体活动类型);然而，电子教练和个性化反馈技术仍处于初级阶段。当前的智能指导策略主要基于手工制作的字符串信息，很少针对每个用户的需求、背景和偏好进行个性化处理。因此，需要更现实、灵活、实用、复杂和吸引人的策略来建模个性化推荐。目的:本研究旨在设计和开发一个本体，对个性化的推荐消息意图、组件(如建议、反馈、论证和后续)和内容(如与推荐活动执行相关的时空内容和对象)进行建模。推理技术将有助于从提出的本体中发现隐含的知识。此外，在提出的本体中，可以将推荐消息分类为不同的类别。 Methods: The ontology was created using Protégé (version 5.5.0) open-source software. We used the Java-based Jena Framework (version 3.16) to build a semantic web application as a proof of concept, which included Resource Description Framework application programming interface, World Wide Web Consortium Web Ontology Language application programming interface, native tuple database, and SPARQL Protocol and Resource Description Framework Query Language query engine. The HermiT (version 1.4.3.x) ontology reasoner available in Protégé 5.x implemented the logical and structural consistency of the proposed ontology. To verify the proposed ontology model, we simulated data for 8 test cases. The personalized recommendation messages were generated based on the processing of personal activity data in combination with contextual weather data and personal preference data. The developed ontology was processed using a query engine against a rule base to generate personalized recommendations. Results: The proposed ontology was implemented in automatic activity coaching to generate and deliver meaningful, personalized lifestyle recommendations. The ontology can be visualized using OWLViz and OntoGraf. In addition, we developed an ontology verification module that behaves similar to a rule-based decision support system to analyze the generation and delivery of personalized recommendation messages following a logical structure. Conclusions: This study led to the creation of a meaningful ontology to generate and model personalized recommendation messages for physical activity coaching. %M 35737439 %R 10.2196/33847 %U https://medinform.www.mybigtv.com/2022/6/e33847 %U https://doi.org/10.2196/33847 %U http://www.ncbi.nlm.nih.gov/pubmed/35737439