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The Runner -- Recommender System of Workout and Nutrition for Runners

机译:跑步者-跑步者健身和营养推荐系统

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摘要

Recommender systems have been gaining popularity and appreciation over the past few years and they kept growing towards a semantic web. Internet users search for more and more facilities to get information and recommendations based on their preferences, experience and expectations. Nowadays, there are many recommender systems on the web for music, movies, diets, products, etc. Some of them use very efficient recommending techniques (ex. Amazon), while others are very simple, based on algorithms that do not always provide relevant or interesting recommendations. The solution we propose is a recommender system for running professionals and amateurs, which is able to provide information to users regarding the workout and the diet that best suits them, based on their profile information, preferences and declared purpose. The solution mixes a social dimension derived from an expanding community with expert knowledge defined within an ontology. Moreover, our model addresses adaptability in terms of personal profile, professional results and unfortunate events that might occur during workouts.
机译:推荐系统在过去的几年中一直受到欢迎和赞赏,并且一直在向语义网发展。互联网用户搜索越来越多的设施,以根据他们的喜好,经验和期望获得信息和建议。如今,网络上有很多音乐,电影,饮食,产品等推荐系统。其中一些使用非常有效的推荐技术(例如Amazon),而另一些则非常简单,其算法并不总是提供相关的或有趣的建议。我们建议的解决方案是针对跑步专业人士和业余爱好者的推荐系统,该系统可以根据用户的个人资料,偏好和声明的目的向用户提供最适合他们的锻炼方法和饮食信息。该解决方案将来自不断扩展的社区的社会维度与在本体中定义的专业知识相结合。此外,我们的模型在锻炼过程中可能会根据个人资料,专业结果和不幸事件处理适应性问题。

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