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Restaurant Recommendation in Vehicle Context Based on Prediction of Traffic Conditions.
- Source :
-
International Journal of Pattern Recognition & Artificial Intelligence . Aug2021, Vol. 35 Issue 10, p1-21. 21p. - Publication Year :
- 2021
-
Abstract
- Restaurant recommendation is one of the most recommendation problems because the result of recommendation varies in different environments. Many methods have been proposed to recommend restaurants in a mobile environment by considering user preference, restaurant attributes, and location. However, there are few restaurant recommender systems according to the internet of vehicles environment. This paper presents a recommender system based on the prediction of traffic conditions in the internet of vehicles environment. This recommender system uses a phased selection method to recommend restaurants. The first stage is to screen restaurants that are on the user's driving route; the second stage is to recommend restaurants from the user attributes, restaurant attributes (with traffic conditions), and vehicle context, using a deep learning model. The experimental evaluation shows that the proposed recommender system is both efficient and effective. [ABSTRACT FROM AUTHOR]
- Subjects :
- *RECOMMENDER systems
*RESTAURANTS
*INTERNET traffic
*DEEP learning
*FORECASTING
Subjects
Details
- Language :
- English
- ISSN :
- 02180014
- Volume :
- 35
- Issue :
- 10
- Database :
- Academic Search Index
- Journal :
- International Journal of Pattern Recognition & Artificial Intelligence
- Publication Type :
- Academic Journal
- Accession number :
- 152395867
- Full Text :
- https://doi.org/10.1142/S0218001421590448