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Titlebook: Recommender Systems in Fashion and Retail; Proceedings of the T Nima Dokoohaki,Shatha Jaradat,Reza Shirvany Conference proceedings 2022 The

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書目名稱Recommender Systems in Fashion and Retail
副標(biāo)題Proceedings of the T
編輯Nima Dokoohaki,Shatha Jaradat,Reza Shirvany
視頻videohttp://file.papertrans.cn/825/824134/824134.mp4
概述Offers the best contributions of the third workshop on recommender systems in fashion and retail.Presents a state-of-the-art view of recommender systems for e-commerce.Provides readers with chapters c
叢書名稱Lecture Notes in Electrical Engineering
圖書封面Titlebook: Recommender Systems in Fashion and Retail; Proceedings of the T Nima Dokoohaki,Shatha Jaradat,Reza Shirvany Conference proceedings 2022 The
描述.This book includes the proceedings of the third workshop on recommender systems in fashion and retail (2021), and it aims to present a state-of-the-art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail, and fashion by presenting readers with chapters covering contributions from academic as well as industrial researchers active within this emerging new field. Recommender systems are often used to solve different complex problems in this scenario, such as product recommendations, size and fit recommendations, and social media-influenced recommendations (outfits worn by influencers)..
出版日期Conference proceedings 2022
關(guān)鍵詞Recommender Systems; Information Retrieval; Information Systems; Machine Learning; AI Artificial Intelli
版次1
doihttps://doi.org/10.1007/978-3-030-94016-4
isbn_softcover978-3-030-94018-8
isbn_ebook978-3-030-94016-4Series ISSN 1876-1100 Series E-ISSN 1876-1119
issn_series 1876-1100
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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978-3-030-94018-8The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Lecture Notes in Electrical Engineeringhttp://image.papertrans.cn/r/image/824134.jpg
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What Users Want? WARHOL: A Generative Model for Recommendationand visual descriptions of novel products. We show that WARHOL can approach the performance of state-of-the-art recommendation models, while being able to generate entirely new products that are relevant to the given user profiles.
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