{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T13:07:15Z","timestamp":1753880835749,"version":"3.41.2"},"reference-count":36,"publisher":"World Scientific Pub Co Pte Ltd","issue":"18","funder":[{"name":"Researchers Supporting Project Number","award":["RSP2024R681"],"award-info":[{"award-number":["RSP2024R681"]}]},{"name":"Project of Hunan Polytechnic of Environment and Biology","award":["TD 2021-03"],"award-info":[{"award-number":["TD 2021-03"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J CIRCUIT SYST COMP"],"published-print":{"date-parts":[[2024,12]]},"abstract":"<jats:p> Recommender systems have been a kind of powerful tool to improve e-commerce benefits. Existing recommender systems mostly employ explicit features of products, such as description and attributes. However, visual characteristics contain fruitful implicit and intuitive information, and are always ignored by existing works. To deal with this issue, this paper proposes a novel intelligent recommender system via visual Transformer (ViT) model and convolutional neural network (CNN) structure. First, the ViT part is utilized to extract visual feature representation. By learning the visual similarity among products, it is expected to obtain a better scene understanding. Then, an improved CNN part is utilized to extract hidden association information from historical behaviors of users. It is expected to better perceive user preference and purchasing characteristics. The combination of two parts constructs the proposed recommender system. Finally, we make performance evaluation for the proposal on real-world e-commerce dataset. The results indicate that the proposal exhibits high recommendation accuracy and efficiency. Compared with other typical algorithms, our proposal can better understand product images and user behaviors, providing more personalized recommendation results. <\/jats:p>","DOI":"10.1142\/s0218126625500057","type":"journal-article","created":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T15:33:55Z","timestamp":1720798435000},"source":"Crossref","is-referenced-by-count":0,"title":["A Visual Transformer and Convolution Neural Network-Based Intelligent Recommender System for e-Commerce Scenes"],"prefix":"10.1142","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6278-3448","authenticated-orcid":false,"given":"Hua","family":"Deng","sequence":"first","affiliation":[{"name":"Hunan Polytechnic of Environment and Biology, Hengyang 421009, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haiying","family":"Huang","sequence":"additional","affiliation":[{"name":"Hunan Polytechnic of Environment and Biology, Hengyang 421009, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6111-8617","authenticated-orcid":false,"given":"Osama","family":"Alfarraj","sequence":"additional","affiliation":[{"name":"Computer Science Department, Community College, King Saud University, Riyadh 11437, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3439-6413","authenticated-orcid":false,"given":"Amr","family":"Tolba","sequence":"additional","affiliation":[{"name":"Computer Science Department, Community College, King Saud University, Riyadh 11437, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2024,9,16]]},"reference":[{"key":"S0218126625500057BIB001","first-page":"173","volume-title":"Recommender Systems Handbook","author":"Zhang S.","year":"2021"},{"key":"S0218126625500057BIB002","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3194536"},{"key":"S0218126625500057BIB003","doi-asserted-by":"publisher","DOI":"10.1007\/s42979-023-01932-9"},{"key":"S0218126625500057BIB004","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.3003802"},{"key":"S0218126625500057BIB005","doi-asserted-by":"publisher","DOI":"10.3390\/electronics12173709"},{"key":"S0218126625500057BIB006","first-page":"973","volume-title":"Recommender Systems Handbook","author":"Deldjoo Y.","year":"2021"},{"key":"S0218126625500057BIB007","doi-asserted-by":"publisher","DOI":"10.1145\/3594315.3594651"},{"key":"S0218126625500057BIB008","doi-asserted-by":"publisher","DOI":"10.1145\/3586075"},{"key":"S0218126625500057BIB009","first-page":"1","volume":"13","author":"Chen F.","year":"2021","journal-title":"ACM Trans. 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