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Published in:
2020 | OriginalPaper | Chapter
Mixed Catering Recommendation Model Based on Context Awareness and User Interest
Authors : Xiaoxu Cui, Rui Huang, Qiang Huang, Zhiyuan Yan, Wentao Liu, Jinshan Pan
Published in: Innovative Computing
Publisher: Springer Singapore
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Abstract
In this paper, the context awareness and recommendation algorithms are studied in depth. From the recommendation of the railway 12306 high-speed rail self-service meal recommendation, the ontology model is firstly designed for the passenger situation and the catering field knowledge, and the corresponding inference rules are designed for knowledge reasoning. context recommendation; then analyze user behavior to obtain preference data, use data filling method to improve traditional user-based collaborative recommendation algorithm; finally, design a hybrid recommendation model combining user context, existing interest preference and potential interest preference. Finally, it is proved by experiments that compared with the single context awareness model and user interest model, the hybrid recommendation model proposed in this paper has a good effect in dealing with dietary recommendation strategies in different situations.