LEADER 03867nam 22007455 450 001 9910551842603321 005 20251225212301.0 010 $a3-030-94016-0 024 7 $a10.1007/978-3-030-94016-4 035 $a(MiAaPQ)EBC6914950 035 $a(Au-PeEL)EBL6914950 035 $a(CKB)21382872700041 035 $a(PPN)261519190 035 $a(BIP)83465837 035 $a(BIP)82452444 035 $a(DE-He213)978-3-030-94016-4 035 $a(EXLCZ)9921382872700041 100 $a20220307d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aRecommender Systems in Fashion and Retail $eProceedings of the Third Workshop at the Recommender Systems Conference (2021) /$fedited by Nima Dokoohaki, Shatha Jaradat, Humberto Jesús Corona Pampín, Reza Shirvany 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (116 pages) 225 1 $aLecture Notes in Electrical Engineering,$x1876-1119 ;$v830 311 08$aPrint version: Dokoohaki, Nima Recommender Systems in Fashion and Retail Cham : Springer International Publishing AG,c2022 9783030940157 320 $aIncludes bibliographical references. 327 $aChapter 1. Using Relational Graph Convolutional Networks to Assign Fashion Communities to Users -- Chapter 2. What Users Want? WARHOL: A Generative Model for Recommendation -- Chapter 3. Knowing When You Don?t Know in Online Fashion: An Uncertainty Aware Size Recommendation Framework -- Chapter 4. SkillSF: In the Sizing Game, Your Size is Your Skill -- Chapter 5. A Critical Analysis of O?ine Evaluation Decisions Against Online Results: A Real-Time Recommendations Case Study -- Chapter 6. Attentive Hierarchical Label Sharing for Enhanced Garment and Attribute Classi?cation of Fashion Imagery -- Chapter 7. Style-based Interactive Eyewear Recommendations. 330 $aThis book includes the proceedings of the third workshop on recommender systems in fashion and retail (2021), and it aims to present a state-of-the-art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail, and fashion by presenting readers with chapters covering contributions from academic as well as industrial researchers active within this emerging new field. Recommender systems are often used to solve different complex problems in this scenario, such as product recommendations, size and fit recommendations, and social media-influenced recommendations (outfits worn by influencers). . 410 0$aLecture Notes in Electrical Engineering,$x1876-1119 ;$v830 606 $aMachine learning 606 $aElectronic commerce 606 $aClothing and dress$xSocial aspects 606 $aHuman body in popular culture 606 $aSocial media 606 $aData protection$xLaw and legislation 606 $aMachine Learning 606 $ae-Commerce and e-Business 606 $aFashion and the Body 606 $aSocial Media 606 $aPrivacy 615 0$aMachine learning. 615 0$aElectronic commerce. 615 0$aClothing and dress$xSocial aspects. 615 0$aHuman body in popular culture. 615 0$aSocial media. 615 0$aData protection$xLaw and legislation. 615 14$aMachine Learning. 615 24$ae-Commerce and e-Business. 615 24$aFashion and the Body. 615 24$aSocial Media. 615 24$aPrivacy. 676 $a005.56 676 $a658.8720285633 702 $aDokoohaki$b Nima 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910551842603321 996 $aRecommender Systems in Fashion and Retail$93071624 997 $aUNINA