Recommender Systems in Fashion and Retail: Proceedings of the Third Workshop at the Recommender Systems Conference (2021)
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer International Publishing AG
2022
|
| Schriftenreihe: | Lecture Notes in Electrical Engineering Series
v.830 |
| Schlagworte: | |
| Online-Zugang: | HWR01 |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 Online-Ressource (116 Seiten) |
| ISBN: | 9783030940164 |
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| 490 | 0 | |a Lecture Notes in Electrical Engineering Series |v v.830 | |
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| 505 | 8 | |a Intro -- Contents -- Graph Recommendations -- Using Relational Graph Convolutional Networks to Assign Fashion Communities to Users -- 1 Introduction -- 2 Proposed Method -- 2.1 Definitions -- 2.2 Method -- 2.3 Model Training -- 2.4 Neural Collaborative Filtering Baseline -- 3 Experiments -- 3.1 Datasets -- 3.2 Hyperparameters and Best Configurations -- 3.3 Results -- 4 Conclusions and Future Work -- References -- Generative Recommendations -- What Users Want? WARHOL: A Generative Model for Recommendation -- 1 Introduction -- 1.1 The Growing Impact of Machine Learning on Quantitative Marketing -- 1.2 Product Innovation as a Machine Learning Problem -- 2 Related Work -- 2.1 Generative Models for New Item Creation: -- 2.2 Generative Models for Image Synthesis -- 3 WARHOL: The Proposed Approach -- 3.1 The WARHOL Model -- 3.2 WARHOL Training -- 4 Experiments -- 4.1 Performance on the Reco Task -- 4.2 Conditional Product Generation -- 5 Conclusions -- 6 Out of Distribution on Fashion Gen -- References -- Sizing and Fit Recommendations -- Knowing When You Don't Know in Online Fashion: An Uncertainty-Aware Size Recommendation Framework -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Size Recommendation Task Formulation -- 3.2 Uncertainty-Based Decision-Making -- 3.3 Uncertainty-Aware Framework for Learning in the Presence of Noise -- 4 Experimental Setup -- 4.1 Dataset, Model, and Evaluation Metric -- 5 Results -- 5.1 Comparison of Uncertainty Metrics -- 5.2 Dataset Pruning and Re-weighting -- 6 Conclusion -- References -- SkillSF: In the Sizing Game, Your Size is Your Skill -- 1 Introduction -- 2 SkillSF -- 2.1 Skill Inference -- 2.2 Size Recommendation -- 2.3 Hyper-parameters -- 3 Experimental Set-Up -- 4 Results -- 4.1 Hyper-Parameters Tuning -- 4.2 Size Recommendation -- 4.3 Size Initialization -- 4.4 Insights into Article Sizes | |
| 505 | 8 | |a 4.5 Return Data -- 5 Discussion and Future Work -- References -- Style-Based Interactive Eyewear Recommendations -- 1 Introduction -- 2 Expert-Based Recommendation and High-Level Expression Attributes -- 3 Implementation Details -- 3.1 Customer and Glasses Feature Extraction -- 3.2 Harmonic and Style Attribute Ranking -- 4 Discussion -- 5 Conclusion -- References -- Fashion Understanding -- A Critical Analysis of Offline Evaluation Decisions Against Online Results: A Real-Time Recommendations Case Study -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 How to Do Offline Evaluation -- 3.2 Dataset -- 3.3 Experimentation -- 4 Results -- 4.1 Live Experiment -- 4.2 Offline Results -- 5 Conclusion -- 6 Future Work -- References -- Attentive Hierarchical Label Sharing for Enhanced Garment and Attribute Classification of Fashion Imagery -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Problem Formulation -- 3.2 Proposed Architectures -- 4 Experimental Setup -- 4.1 Datasets -- 4.2 Evaluation -- 5 Results -- 5.1 Object Type Detection -- 5.2 Category and Attribute Classification -- 6 Conclusions -- References | |
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| 700 | 1 | |a Corona Pampín, Humberto Jesús |e Sonstige |4 oth | |
| 700 | 1 | |a Shirvany, Reza |e Sonstige |4 oth | |
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Datensatz im Suchindex
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| author | Dokoohaki, Nima |
| author_facet | Dokoohaki, Nima |
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| author_sort | Dokoohaki, Nima |
| author_variant | n d nd |
| building | Verbundindex |
| bvnumber | BV048920987 |
| collection | ZDB-30-PQE |
| contents | Intro -- Contents -- Graph Recommendations -- Using Relational Graph Convolutional Networks to Assign Fashion Communities to Users -- 1 Introduction -- 2 Proposed Method -- 2.1 Definitions -- 2.2 Method -- 2.3 Model Training -- 2.4 Neural Collaborative Filtering Baseline -- 3 Experiments -- 3.1 Datasets -- 3.2 Hyperparameters and Best Configurations -- 3.3 Results -- 4 Conclusions and Future Work -- References -- Generative Recommendations -- What Users Want? WARHOL: A Generative Model for Recommendation -- 1 Introduction -- 1.1 The Growing Impact of Machine Learning on Quantitative Marketing -- 1.2 Product Innovation as a Machine Learning Problem -- 2 Related Work -- 2.1 Generative Models for New Item Creation: -- 2.2 Generative Models for Image Synthesis -- 3 WARHOL: The Proposed Approach -- 3.1 The WARHOL Model -- 3.2 WARHOL Training -- 4 Experiments -- 4.1 Performance on the Reco Task -- 4.2 Conditional Product Generation -- 5 Conclusions -- 6 Out of Distribution on Fashion Gen -- References -- Sizing and Fit Recommendations -- Knowing When You Don't Know in Online Fashion: An Uncertainty-Aware Size Recommendation Framework -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Size Recommendation Task Formulation -- 3.2 Uncertainty-Based Decision-Making -- 3.3 Uncertainty-Aware Framework for Learning in the Presence of Noise -- 4 Experimental Setup -- 4.1 Dataset, Model, and Evaluation Metric -- 5 Results -- 5.1 Comparison of Uncertainty Metrics -- 5.2 Dataset Pruning and Re-weighting -- 6 Conclusion -- References -- SkillSF: In the Sizing Game, Your Size is Your Skill -- 1 Introduction -- 2 SkillSF -- 2.1 Skill Inference -- 2.2 Size Recommendation -- 2.3 Hyper-parameters -- 3 Experimental Set-Up -- 4 Results -- 4.1 Hyper-Parameters Tuning -- 4.2 Size Recommendation -- 4.3 Size Initialization -- 4.4 Insights into Article Sizes 4.5 Return Data -- 5 Discussion and Future Work -- References -- Style-Based Interactive Eyewear Recommendations -- 1 Introduction -- 2 Expert-Based Recommendation and High-Level Expression Attributes -- 3 Implementation Details -- 3.1 Customer and Glasses Feature Extraction -- 3.2 Harmonic and Style Attribute Ranking -- 4 Discussion -- 5 Conclusion -- References -- Fashion Understanding -- A Critical Analysis of Offline Evaluation Decisions Against Online Results: A Real-Time Recommendations Case Study -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 How to Do Offline Evaluation -- 3.2 Dataset -- 3.3 Experimentation -- 4 Results -- 4.1 Live Experiment -- 4.2 Offline Results -- 5 Conclusion -- 6 Future Work -- References -- Attentive Hierarchical Label Sharing for Enhanced Garment and Attribute Classification of Fashion Imagery -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Problem Formulation -- 3.2 Proposed Architectures -- 4 Experimental Setup -- 4.1 Datasets -- 4.2 Evaluation -- 5 Results -- 5.1 Object Type Detection -- 5.2 Category and Attribute Classification -- 6 Conclusions -- References |
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| dewey-full | 658.8720285633 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
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| dewey-search | 658.8720285633 |
| dewey-sort | 3658.8720285633 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| format | Electronic eBook |
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| id | DE-604.BV048920987 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T21:55:16Z |
| indexdate | 2024-07-10T09:49:54Z |
| institution | BVB |
| isbn | 9783030940164 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034185078 |
| oclc_num | 1303085950 |
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| physical | 1 Online-Ressource (116 Seiten) |
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| series2 | Lecture Notes in Electrical Engineering Series |
| spelling | Dokoohaki, Nima Verfasser aut Recommender Systems in Fashion and Retail Proceedings of the Third Workshop at the Recommender Systems Conference (2021) Cham Springer International Publishing AG 2022 ©2022 1 Online-Ressource (116 Seiten) txt rdacontent c rdamedia cr rdacarrier Lecture Notes in Electrical Engineering Series v.830 Description based on publisher supplied metadata and other sources Intro -- Contents -- Graph Recommendations -- Using Relational Graph Convolutional Networks to Assign Fashion Communities to Users -- 1 Introduction -- 2 Proposed Method -- 2.1 Definitions -- 2.2 Method -- 2.3 Model Training -- 2.4 Neural Collaborative Filtering Baseline -- 3 Experiments -- 3.1 Datasets -- 3.2 Hyperparameters and Best Configurations -- 3.3 Results -- 4 Conclusions and Future Work -- References -- Generative Recommendations -- What Users Want? WARHOL: A Generative Model for Recommendation -- 1 Introduction -- 1.1 The Growing Impact of Machine Learning on Quantitative Marketing -- 1.2 Product Innovation as a Machine Learning Problem -- 2 Related Work -- 2.1 Generative Models for New Item Creation: -- 2.2 Generative Models for Image Synthesis -- 3 WARHOL: The Proposed Approach -- 3.1 The WARHOL Model -- 3.2 WARHOL Training -- 4 Experiments -- 4.1 Performance on the Reco Task -- 4.2 Conditional Product Generation -- 5 Conclusions -- 6 Out of Distribution on Fashion Gen -- References -- Sizing and Fit Recommendations -- Knowing When You Don't Know in Online Fashion: An Uncertainty-Aware Size Recommendation Framework -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Size Recommendation Task Formulation -- 3.2 Uncertainty-Based Decision-Making -- 3.3 Uncertainty-Aware Framework for Learning in the Presence of Noise -- 4 Experimental Setup -- 4.1 Dataset, Model, and Evaluation Metric -- 5 Results -- 5.1 Comparison of Uncertainty Metrics -- 5.2 Dataset Pruning and Re-weighting -- 6 Conclusion -- References -- SkillSF: In the Sizing Game, Your Size is Your Skill -- 1 Introduction -- 2 SkillSF -- 2.1 Skill Inference -- 2.2 Size Recommendation -- 2.3 Hyper-parameters -- 3 Experimental Set-Up -- 4 Results -- 4.1 Hyper-Parameters Tuning -- 4.2 Size Recommendation -- 4.3 Size Initialization -- 4.4 Insights into Article Sizes 4.5 Return Data -- 5 Discussion and Future Work -- References -- Style-Based Interactive Eyewear Recommendations -- 1 Introduction -- 2 Expert-Based Recommendation and High-Level Expression Attributes -- 3 Implementation Details -- 3.1 Customer and Glasses Feature Extraction -- 3.2 Harmonic and Style Attribute Ranking -- 4 Discussion -- 5 Conclusion -- References -- Fashion Understanding -- A Critical Analysis of Offline Evaluation Decisions Against Online Results: A Real-Time Recommendations Case Study -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 How to Do Offline Evaluation -- 3.2 Dataset -- 3.3 Experimentation -- 4 Results -- 4.1 Live Experiment -- 4.2 Offline Results -- 5 Conclusion -- 6 Future Work -- References -- Attentive Hierarchical Label Sharing for Enhanced Garment and Attribute Classification of Fashion Imagery -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Problem Formulation -- 3.2 Proposed Architectures -- 4 Experimental Setup -- 4.1 Datasets -- 4.2 Evaluation -- 5 Results -- 5.1 Object Type Detection -- 5.2 Category and Attribute Classification -- 6 Conclusions -- References Recommender systems (Information filtering) Jaradat, Shatha Sonstige oth Corona Pampín, Humberto Jesús Sonstige oth Shirvany, Reza Sonstige oth Erscheint auch als Druck-Ausgabe Dokoohaki, Nima Recommender Systems in Fashion and Retail Cham : Springer International Publishing AG,c2022 9783030940157 |
| spellingShingle | Dokoohaki, Nima Recommender Systems in Fashion and Retail Proceedings of the Third Workshop at the Recommender Systems Conference (2021) Intro -- Contents -- Graph Recommendations -- Using Relational Graph Convolutional Networks to Assign Fashion Communities to Users -- 1 Introduction -- 2 Proposed Method -- 2.1 Definitions -- 2.2 Method -- 2.3 Model Training -- 2.4 Neural Collaborative Filtering Baseline -- 3 Experiments -- 3.1 Datasets -- 3.2 Hyperparameters and Best Configurations -- 3.3 Results -- 4 Conclusions and Future Work -- References -- Generative Recommendations -- What Users Want? WARHOL: A Generative Model for Recommendation -- 1 Introduction -- 1.1 The Growing Impact of Machine Learning on Quantitative Marketing -- 1.2 Product Innovation as a Machine Learning Problem -- 2 Related Work -- 2.1 Generative Models for New Item Creation: -- 2.2 Generative Models for Image Synthesis -- 3 WARHOL: The Proposed Approach -- 3.1 The WARHOL Model -- 3.2 WARHOL Training -- 4 Experiments -- 4.1 Performance on the Reco Task -- 4.2 Conditional Product Generation -- 5 Conclusions -- 6 Out of Distribution on Fashion Gen -- References -- Sizing and Fit Recommendations -- Knowing When You Don't Know in Online Fashion: An Uncertainty-Aware Size Recommendation Framework -- 1 Introduction -- 2 Related Work -- 3 Approach -- 3.1 Size Recommendation Task Formulation -- 3.2 Uncertainty-Based Decision-Making -- 3.3 Uncertainty-Aware Framework for Learning in the Presence of Noise -- 4 Experimental Setup -- 4.1 Dataset, Model, and Evaluation Metric -- 5 Results -- 5.1 Comparison of Uncertainty Metrics -- 5.2 Dataset Pruning and Re-weighting -- 6 Conclusion -- References -- SkillSF: In the Sizing Game, Your Size is Your Skill -- 1 Introduction -- 2 SkillSF -- 2.1 Skill Inference -- 2.2 Size Recommendation -- 2.3 Hyper-parameters -- 3 Experimental Set-Up -- 4 Results -- 4.1 Hyper-Parameters Tuning -- 4.2 Size Recommendation -- 4.3 Size Initialization -- 4.4 Insights into Article Sizes 4.5 Return Data -- 5 Discussion and Future Work -- References -- Style-Based Interactive Eyewear Recommendations -- 1 Introduction -- 2 Expert-Based Recommendation and High-Level Expression Attributes -- 3 Implementation Details -- 3.1 Customer and Glasses Feature Extraction -- 3.2 Harmonic and Style Attribute Ranking -- 4 Discussion -- 5 Conclusion -- References -- Fashion Understanding -- A Critical Analysis of Offline Evaluation Decisions Against Online Results: A Real-Time Recommendations Case Study -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 How to Do Offline Evaluation -- 3.2 Dataset -- 3.3 Experimentation -- 4 Results -- 4.1 Live Experiment -- 4.2 Offline Results -- 5 Conclusion -- 6 Future Work -- References -- Attentive Hierarchical Label Sharing for Enhanced Garment and Attribute Classification of Fashion Imagery -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Problem Formulation -- 3.2 Proposed Architectures -- 4 Experimental Setup -- 4.1 Datasets -- 4.2 Evaluation -- 5 Results -- 5.1 Object Type Detection -- 5.2 Category and Attribute Classification -- 6 Conclusions -- References Recommender systems (Information filtering) |
| title | Recommender Systems in Fashion and Retail Proceedings of the Third Workshop at the Recommender Systems Conference (2021) |
| title_auth | Recommender Systems in Fashion and Retail Proceedings of the Third Workshop at the Recommender Systems Conference (2021) |
| title_exact_search | Recommender Systems in Fashion and Retail Proceedings of the Third Workshop at the Recommender Systems Conference (2021) |
| title_exact_search_txtP | Recommender Systems in Fashion and Retail Proceedings of the Third Workshop at the Recommender Systems Conference (2021) |
| title_full | Recommender Systems in Fashion and Retail Proceedings of the Third Workshop at the Recommender Systems Conference (2021) |
| title_fullStr | Recommender Systems in Fashion and Retail Proceedings of the Third Workshop at the Recommender Systems Conference (2021) |
| title_full_unstemmed | Recommender Systems in Fashion and Retail Proceedings of the Third Workshop at the Recommender Systems Conference (2021) |
| title_short | Recommender Systems in Fashion and Retail |
| title_sort | recommender systems in fashion and retail proceedings of the third workshop at the recommender systems conference 2021 |
| title_sub | Proceedings of the Third Workshop at the Recommender Systems Conference (2021) |
| topic | Recommender systems (Information filtering) |
| topic_facet | Recommender systems (Information filtering) |
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