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    Computer Science Department, Politehnica University of Bucharest
    Research Institute for Artificial Intelligence

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

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    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.

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    Description

    Title : The Runner -- Recommender System of Workout and Nutrition for Runners
    Author(s) : Mihnea Donciu, Madalina Ionita, Mihai Dascalu, Stefan Trausan-Matu
    Abstract : 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.
    Subject : unspecified
    Area : Other
    Language : English
    Year : 2011

    Affiliations Computer Science Department, Politehnica University of Bucharest
    Journal : 2011 13th International Symposium on Symbolic and Numeric Algori
    Publisher : IEEE
    Pages : 230 - 238
    Url : http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6169585
    Isbn : 978-1-4673-0207-4
    Doi : 10.1109/SYNASC.2011.18

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    Stefan's Peer Evaluation activity

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