神经协同过滤智能商业选址方法

Nuo Li, Bin Guo, Yan Liu, Yao Jing, Zhi Wen Yu

科研成果: 期刊稿件文章同行评审

摘要

A new neural collaborative filtering method, NCF-RS, was proposed based on the framework of neural collaborative filtering (NCF). In order to discover the relationship between store category and site, the linear relationship between store categories and sites was studied by matrix decomposition, the non-linear and in-depth relationship between store categories and sites was studied by deep learning multi-layer perceptron, then the two relationships were combined for the final results. Restaurants' data and POI data in Beijing were used to evaluate the performance of NCF-RS. Results indicate that NCF-RS has better performance in intelligent commercial site recommendation than other advanced deep learning methods and collaborative filtering methods, and can take linear and nonlinear relationships into better consideration.

投稿的翻译标题Intelligent commercial site recommendation with neural collaborative filtering
源语言繁体中文
页(从-至)1788-1794
页数7
期刊Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science)
53
9
DOI
出版状态已出版 - 1 9月 2019

关键词

  • Commercial site recommendation
  • Matrix decomposition
  • Multi-layer perceptron
  • Neural collaborative filtering (NCF)
  • Recommendation system

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