{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T15:07:54Z","timestamp":1770044874166,"version":"3.49.0"},"reference-count":29,"publisher":"SAGE Publications","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2021,9,15]]},"abstract":"<jats:p>In the development of product design, one of the elements of market competition for products is to meet the Kansei needs of users. Compared to features, users pay more attention to whether products can match their emotions, which is Kansei needs. The product developers are eager to get the Kansei needs of users more accurately and conveniently. This paper takes the computer cloud platform as the carrier and based on the collaborative filtering algorithm. We used personalized double matrix recommendation algorithm as the core, and the adjectives dimensionality reduction method to filter the image tags to simplify the users\u2019 rating process and improve the recommendation efficiency. Finally, we construct a Kansei needs acquisition model to quickly and easily obtain the Kansei needs of users. We verify the model using the air purifier as a subject. The results of the case show that the model can find out the user\u2019s Kansei needs more quickly. When the data is more, the prediction will be more accurate and timely.<\/jats:p>","DOI":"10.3233\/jifs-191241","type":"journal-article","created":{"date-parts":[[2021,7,7]],"date-time":"2021-07-07T05:24:42Z","timestamp":1625635482000},"page":"3809-3820","source":"Crossref","is-referenced-by-count":3,"title":["The acquisition method of the user\u2019s Kansei needs based on double matrix recommendation algorithm"],"prefix":"10.1177","volume":"41","author":[{"given":"Ning","family":"Xie","sequence":"first","affiliation":[{"name":"Shaanxi Engineering Laboratory for Industrial Design, Northwestern Polytechnical University, Xi\u2019an, Shaanxi, China"}]},{"given":"Dengkai","family":"Chen","sequence":"additional","affiliation":[{"name":"Shaanxi Engineering Laboratory for Industrial Design, Northwestern Polytechnical University, Xi\u2019an, Shaanxi, China"}]},{"given":"Yu","family":"Fan","sequence":"additional","affiliation":[{"name":"Shaanxi Engineering Laboratory for Industrial Design, Northwestern Polytechnical University, Xi\u2019an, Shaanxi, China"}]},{"given":"Mengya","family":"Zhu","sequence":"additional","affiliation":[{"name":"Shaanxi Engineering Laboratory for Industrial Design, Northwestern Polytechnical University, Xi\u2019an, Shaanxi, China"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-191241_ref1","doi-asserted-by":"crossref","first-page":"63","DOI":"10.3233\/JIFS-179064","article-title":"Intelligent system for products personalization and design using genetic algorithm","volume":"37","author":"Song","year":"2019","journal-title":"Journal of Intelligent & Fuzzy Systems"},{"issue":"2011","key":"10.3233\/JIFS-191241_ref2","first-page":"11382","article-title":"A classification-based Kansei engineering system for modeling consumers\u2019 affective responses and analyzing product form features","volume":"38","author":"Yang","journal-title":"Expert Systems with 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