Context-aware Recommender System Based on Content Filtering
- Publication Type
- Conference abstract/paper published in a peer review journal
- Authors
- Mai Iyad Abusair
- Mohammad Sharaf
- Mosab Bozeya
- Abdulrhman Beiruti
The use of context is important in interactive applications. It is essential for applications where the user’s context is changing quickly. Mobile applications can benefit from context awareness since they incur to context changes during their execution. Moreover, recommender systems can benefit from context awareness to produce more relevant recommendations by adapting them to the specific contextual situation of the user. This paper suggests an approach for building context aware recommender system. The approach implements user profile, content-based filtering and uses contextual information to create more beneficial recommender system. To evaluate our approach, we ran an experimentation on a mobile application implemented for the food and delivery services.
- Title
- 2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT)
- Publisher
- IEEE
- Publisher Country
- Azerbaijan
- Indexing
- Scopus
- Impact Factor
- None
- Publication Type
- Both (Printed and Online)
- Volume
- 15
- Year
- 2021
- Pages
- --