【摘 要】
：
In recent years,online reservation systems of country hotel have become increasingly popular in rural areas.How to accurately recommend the houses of country hotel to the users is an urgent problem to be solved.Aiming at the problem of cold start and data
【机 构】
：
School of Computer Science and Information Engineering,Hubei University,Wuhan 430000,China;Hubei Pro
论文部分内容阅读
In recent years,online reservation systems of country hotel have become increasingly popular in rural areas.How to accurately recommend the houses of country hotel to the users is an urgent problem to be solved.Aiming at the problem of cold start and data sparseness in recommendation,a Hybrid Recommen-dation method based on Graph Embedding (HRGE)is proposed.First,three types of network are built,including user-user network based on user tag,house-house network based on house tag,and user-user net-work based on user behavior.Then,by using the method of graph embedding,three types of network are respectively embedded into low-dimensional vec-tors to obtain the characterization vectors of nodes.Fi-nally,these characterization vectors are used to make a hybrid recommendation.The datasets in this paper are derived from the Country Hotel Reservation Sys-tem in Guizhou Province.The experimental results show that,compared with traditional recommendation algorithms,the comprehensive evaluation index (F1)of the HRGE is improved by 20％ and the Mean Aver-age Precision (MAP) is increased by 11％.
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