Abstract: Selecting the most appropriate places under differ-ent context is important contribution nowadays for people who visit places for the first time. The aim of the work in this paper is to make a context-aware recommender system, which recom-mends places to users based on the current weather, the time of the day, and the user’s mood. This Context-aware Recommender System will determine the current weather and time of the day in a user’s location. Then, it gets places that are appropriate to context state in the user’s location. Also, Recommender system takes the current user’s mood and then selects the location that the user should go. Places are recommended based on what other users have visited in the similar context conditions. Recommender system puts rates for each place in each context for each user. The place’s rates are calculated by The Genetic algorithm, based on Gamma function. Finally,mobile application was implemented in the context-aware recommender system.

Soha A.El-Moemen Mohamed, Taysir Hassan A.Soliman and Adel A.Sewisy. “A Context-Aware Recommender System for Personalized Places in Mobile Applications”. International Journal of Advanced Computer Science and Applications (IJACSA) 7.3 (2016). http://dx.doi.org/10.14569/IJACSA.2016.070360

@article{Mohamed2016,
title = {A Context-Aware Recommender System for Personalized Places in Mobile Applications},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070360},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070360},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {3},
author = {Soha A.El-Moemen Mohamed and Taysir Hassan A.Soliman and Adel A.Sewisy}
}