Abstract
Active life style promotes healthy aging, and participation in social and physical activities improves aging people well-being. Nowadays, new media sources advertise large number of activities and for all age categories. These medias, however, are not adapted to the aging population. The paper presents a context-aware in-person social activity recommendation system for aging people named QueFaire. QueFaire interprets natural language descriptions of activities in social media and proposes suitable activities to aging people using fuzzy logic engine, taking in consideration user-profile and contextual information. Moreover, QueFaire provides support to help reach the location of a social activity.
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Ponce, V., Deschamps, JP., Giroux, LP., Salehi, F., Abdulrazak, B. (2015). QueFaire: Context-Aware in-Person Social Activity Recommendation System for Active Aging. In: Geissbühler, A., Demongeot, J., Mokhtari, M., Abdulrazak, B., Aloulou, H. (eds) Inclusive Smart Cities and e-Health. ICOST 2015. Lecture Notes in Computer Science(), vol 9102. Springer, Cham. https://doi.org/10.1007/978-3-319-19312-0_6
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