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This algorithm considers information influence attenuation over time, introduces an information retention period based on the information half\u2010value period, and proposes a time\u2010weighted function, which is applied to the nearest neighbor selection and score prediction to assign different time weights to the scores. In addition, to further improve the quality of the nearest neighbor selection and alleviate the problem of data sparsity, a method of calculating users\u2019 sentiment tendency by analysis of user review features is proposed to mine users\u2019 attitudes about the reviewed items, which expands the score matrix. The time factor and sentiment tendency are then integrated into the <jats:italic>K<\/jats:italic>\u2010means clustering algorithm to select the nearest neighbor. A hybrid collaborative filtering model (TWCHR) based on the improved <jats:italic>K<\/jats:italic>\u2010means clustering algorithm is then proposed, by combining item\u2010based and user\u2010based collaborative filtering. Finally, the experimental results show that the proposed algorithm can address the time effect and sentiment analysis in recommendations and improve the predictive performance of the model.<\/jats:p>","DOI":"10.1155\/2021\/6635202","type":"journal-article","created":{"date-parts":[[2021,3,8]],"date-time":"2021-03-08T18:05:56Z","timestamp":1615226756000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Research on Hybrid Collaborative Filtering Recommendation Algorithm Based on the Time Effect and Sentiment Analysis"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1831-9872","authenticated-orcid":false,"given":"Xibin","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2951-2910","authenticated-orcid":false,"given":"Zhenyu","family":"Dai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2242-6646","authenticated-orcid":false,"given":"Hui","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3486-9604","authenticated-orcid":false,"given":"Jianfeng","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2021,3,8]]},"reference":[{"key":"e_1_2_12_1_2","doi-asserted-by":"publisher","DOI":"10.1145\/3357154"},{"key":"e_1_2_12_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.02.052"},{"key":"e_1_2_12_3_2","doi-asserted-by":"crossref","unstructured":"DingY.andLiX. 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