Closed-Loop Deep Learning Improves E-Commerce Pricing and Forecasting
A new closed-loop framework using Transformer-based forecasting and Proximal Policy Optimization improves e-commerce dynamic pricing and demand accuracy by integrating ...
A new closed-loop framework using Transformer-based forecasting and Proximal Policy Optimization improves e-commerce dynamic pricing and demand accuracy by integrating ...
A market audit across selected Chinese online grocery listings found ingredient-absence or non-addition wording in 10 percent of evaluable records ...
A configurational analysis of 240 digital agricultural producers across China reveals that high marketing performance is achieved through three distinct ...
A study of 348 UK e-commerce customers found that chatbot anthropomorphism and ease of use significantly increase user satisfaction and ...
A bibliometric mapping of 1,054 open-access journal articles from 2020 to 2025 reveals that explosive publication growth in digital and ...
A long-term study of Quanzhou, China, reveals that e-commerce initially improves land-use efficiency in compact clusters but drives outward urban ...
A panel study across 24 European Union countries found that online consumption among adults aged 55 to 74 shows heterogeneous ...
A joint deep learning framework called J-SUP unifies aspect-based sentiment analysis and consumer preference profiling within a shared Transformer architecture ...
A new study reports a quantum-inspired recommendation system combining fuzzy clustering, generative adversarial networks, and a dandelion-based optimizer that achieved ...
A qualitative study of 41 Spanish food purchasers finds broad sympathy for smallholders but little willingness to buy fresh produce ...
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© 2026 Scienmag - Science Magazine