Recommender system for healthy and enjoyable activities based on location data

التفاصيل البيبلوغرافية
العنوان: Recommender system for healthy and enjoyable activities based on location data
المؤلفون: Capdevila Solanich, Albert
المساهمون: Universitat Politècnica de Catalunya, Universiteit Gent, De Pessemier, Toon
بيانات النشر: Universitat Politècnica de Catalunya, 2023.
سنة النشر: 2023
مصطلحات موضوعية: Sistemes de recomanació basats en contingut, Aplicacions mòbils, Content-based recommender systems, Aplicació mòbil, Physical activity, Informàtica::Enginyeria del software [Àrees temàtiques de la UPC], Mobile apps, Recommender systems (Information filtering), Recommender systems, Mobile application, Sistemes de recomanació, Activitat física, Sistemes recomanadors (Filtratge d'informació)
الوصف: Technological progress in recent years has led to the automation of many of the tasks we perform in our daily life. Massive use of digital devices nowadays means that a lot of information could be collected, for example about our habits and behaviours. All this data can be used to develop technological solutions, such as recommender systems, that analyse our behaviour and can predict future scenarios that make our lives easier. The goal of this project is to create a mobile recommender system on Android that tries to motivate users to do more physical activity by offering enjoyable POIs (Points Of Interest) such as parks, museums, tourist attractions... It should be noted that most recommender systems are only based on preferences, but in this project, the context of the user will also be used to make suggestions. In other words, the user's location will be obtained in real time in order to propose different points of interest in their surroundings that are close to their personal interests.
وصف الملف: application/pdf
اللغة: English
URL الوصول: https://explore.openaire.eu/search/publication?articleId=od______3484::6e9054c4a720c82f41fa4ef4cdaed96e
https://hdl.handle.net/2117/384760
Rights: OPEN
رقم الانضمام: edsair.od......3484..6e9054c4a720c82f41fa4ef4cdaed96e
قاعدة البيانات: OpenAIRE