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However, sparse individual purchase behavior hinders the identification of group preferences. Therefore, a novel inspiration recommendation (IR) system based on multi-level mining of user behavior data is proposed. Firstly, the K-means algorithm is employed to cluster users based on a variety of features. The fixed association rule is then applied to filter and identify relevant subsets, forming the foundational basis for constructing a user portrait. The Nonlinear Bayesian Personalized Ranking (NBPR) is constructed to explore common preferences using explicit feedback. Finally, the item preference matrix is enriched with implicit feedback to compile a comprehensive recommendation list that caters to group preferences. Using a multi-user joint evaluation approach, we compare the performance of IR with baseline models across multiple metrics. This comparison demonstrates the robust reliability of the IR system and its ability to prioritize ISAD with preference-aligned groups. Our research overcomes data sparsity in the automotive recommendation system, providing a new method for embedding human elements in decision support systems.<\/jats:p>","DOI":"10.3390\/systems12110491","type":"journal-article","created":{"date-parts":[[2024,11,14]],"date-time":"2024-11-14T10:47:53Z","timestamp":1731581273000},"page":"491","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["An Inspiration Recommendation System for Automotive Styling Design Based on User Behavior Data and Group Preferences"],"prefix":"10.3390","volume":"12","author":[{"given":"Wanxin","family":"Cai","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering, Guizhou University, Guiyang 550000, China"},{"name":"Institute of Twenty-Seventh, China Electronics Technology Group Corporation, Zhengzhou 450000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingqing","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Guizhou University, Guiyang 550000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5274-6985","authenticated-orcid":false,"given":"Li","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Guizhou University, Guiyang 550000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"121289","DOI":"10.1016\/j.eswa.2023.121289","article-title":"A cognitive analysis-based key concepts derivation approach for product design","volume":"236","author":"Li","year":"2024","journal-title":"Expert Syst. 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