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The idea is to fuse the embedded vectors of users and items into mapping vectors (or matrices) of different shapes through different methods, and learn the interactive relationship between users and items through the neural network model with attention mechanism. Experimental results show that compared with traditional analytical methods, multiple dimension analysis can more comprehensively explore the interaction between users and items, and the attention mechanism can greatly improve the analytical ability of the model.<\/jats:p>","DOI":"10.4018\/ijmcmc.2020010103","type":"journal-article","created":{"date-parts":[[2020,2,7]],"date-time":"2020-02-07T14:25:21Z","timestamp":1581085521000},"page":"42-57","source":"Crossref","is-referenced-by-count":1,"title":["A Hybrid Recommender Method Based on Multiple Dimension Attention Analysis"],"prefix":"10.4018","volume":"11","author":[{"given":"Minghu","family":"Wu","sequence":"first","affiliation":[{"name":"Hubei Collaborative Innovation Center for High-efficiency Utilization of Solar Energy, Hubei University of Technology, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Songnan","family":"Lv","sequence":"additional","affiliation":[{"name":"Hubei University of technology, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunyan","family":"Zeng","sequence":"additional","affiliation":[{"name":"Hubei University of technology, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhifeng","family":"Wang","sequence":"additional","affiliation":[{"name":"Central China Normal University, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nan","family":"Zhao","sequence":"additional","affiliation":[{"name":"Hubei Collaborative Innovation Center for High-efficiency Utilization of Solar Energy, Hubei University of Technology, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Zhu","sequence":"additional","affiliation":[{"name":"Hubei Collaborative Innovation Center for High-efficiency Utilization of Solar Energy, Hubei University of Technology, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan","family":"Wang","sequence":"additional","affiliation":[{"name":"Hubei Collaborative Innovation Center for High-efficiency Utilization of Solar Energy, Hubei University of Technology, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ming","family":"Wu","sequence":"additional","affiliation":[{"name":"Hubei University of technology, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJMCMC.2020010103-0","article-title":"Neural machine translation by jointly learning to align and translate.","author":"D.Bahdanau","year":"2014","journal-title":"Computer Science"},{"key":"IJMCMC.2020010103-1","first-page":"1","article-title":"Item2vec: neural item embedding for collaborative filtering.","author":"O.Barkan","year":"2016","journal-title":"Proceedings of the 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)"},{"key":"IJMCMC.2020010103-2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2013.03.012"},{"key":"IJMCMC.2020010103-3","doi-asserted-by":"publisher","DOI":"10.1023\/A:1021240730564"},{"key":"IJMCMC.2020010103-4","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1145\/2988450.2988454","article-title":"Wide & deep learning for recommender systems.","author":"H. 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