1. Restaurant Recommendation in Vehicle Context Based on Prediction of Traffic Conditions.
- Author
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Wang, Zehong, Liu, Jianhua, Shen, Shigen, and Li, Minglu
- Subjects
- *
RECOMMENDER systems , *RESTAURANTS , *INTERNET traffic , *DEEP learning , *FORECASTING - 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]
- Published
- 2021
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