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Implementation of digitalized technologies for fashion industry 4.0: Opportunities and challenges
The Sustainable Development Goals of the United Nations prioritize sustainability by 2030.
The fashion industry is one most substantial manufacturing industries that generate an …
The fashion industry is one most substantial manufacturing industries that generate an …
A review of modern recommender systems using generative models (gen-recsys)
Traditional recommender systems typically use user-item rating histories as their main data
source. However, deep generative models now have the capability to model and sample …
source. However, deep generative models now have the capability to model and sample …
M6-rec: Generative pretrained language models are open-ended recommender systems
Industrial recommender systems have been growing increasingly complex, may
involve\emph {diverse domains} such as e-commerce products and user-generated …
involve\emph {diverse domains} such as e-commerce products and user-generated …
Stylegan-human: A data-centric odyssey of human generation
Unconditional human image generation is an important task in vision and graphics, enabling
various applications in the creative industry. Existing studies in this field mainly focus on …
various applications in the creative industry. Existing studies in this field mainly focus on …
BERT4Rec: Sequential recommendation with bidirectional encoder representations from transformer
Modeling users' dynamic preferences from their historical behaviors is challenging and
crucial for recommendation systems. Previous methods employ sequential neural networks …
crucial for recommendation systems. Previous methods employ sequential neural networks …
Self-attentive sequential recommendation
Sequential dynamics are a key feature of many modern recommender systems, which seek
to capture the'context'of users' activities on the basis of actions they have performed recently …
to capture the'context'of users' activities on the basis of actions they have performed recently …
Mining latent structures for multimedia recommendation
Multimedia content is of predominance in the modern Web era. Investigating how users
interact with multimodal items is a continuing concern within the rapid development of …
interact with multimodal items is a continuing concern within the rapid development of …
A comprehensive survey on multimodal recommender systems: Taxonomy, evaluation, and future directions
Recommendation systems have become popular and effective tools to help users discover
their interesting items by modeling the user preference and item property based on implicit …
their interesting items by modeling the user preference and item property based on implicit …
A survey on adversarial recommender systems: from attack/defense strategies to generative adversarial networks
Latent-factor models (LFM) based on collaborative filtering (CF), such as matrix factorization
(MF) and deep CF methods, are widely used in modern recommender systems (RS) due to …
(MF) and deep CF methods, are widely used in modern recommender systems (RS) due to …
Customer models for artificial intelligence-based decision support in fashion online retail supply chains
Fashion is a global, multi-trillion dollar industry devoted to producing and selling clothing,
footwear, and accessories to individuals or groups of people. Its sheer numbers, together …
footwear, and accessories to individuals or groups of people. Its sheer numbers, together …