Demand forecasting for fashion products: A systematic review
K Swaminathan, R Venkitasubramony - International Journal of Forecasting, 2024 - Elsevier
Fashion is one of the most challenging categories for forecasting demand. Our study
provides a systematic literature review of the different forecasting techniques used in the …
provides a systematic literature review of the different forecasting techniques used in the …
FC-GAGA: Fully connected gated graph architecture for spatio-temporal traffic forecasting
BN Oreshkin, A Amini, L Coyle, M Coates - Proceedings of the AAAI …, 2021 - ojs.aaai.org
Forecasting of multivariate time-series is an important problem that has applications in traffic
management, cellular network configuration, and quantitative finance. A special case of the …
management, cellular network configuration, and quantitative finance. A special case of the …
Attention based multi-modal new product sales time-series forecasting
Trend driven retail industries such as fashion, launch substantial new products every
season. In such a scenario, an accurate demand forecast for these newly launched products …
season. In such a scenario, an accurate demand forecast for these newly launched products …
Multimodal Quasi-AutoRegression: Forecasting the visual popularity of new fashion products
Estimating the preferences of consumers is of utmost importance for the fashion industry as
appropriately leveraging this information can be beneficial in terms of profit. Trend detection …
appropriately leveraging this information can be beneficial in terms of profit. Trend detection …
Well googled is half done: Multimodal forecasting of new fashion product sales with image‐based google trends
New fashion product sales forecasting is a challenging problem that involves many business
dynamics and cannot be solved by classical forecasting approaches. In this paper, we …
dynamics and cannot be solved by classical forecasting approaches. In this paper, we …
Fashion informatics of the Big 4 Fashion Weeks using topic modeling and sentiment analysis
YH Choi, S Yoon, B Xuan, SYT Lee, KH Lee - Fashion and Textiles, 2021 - Springer
This study used several informatics techniques to analyze consumer-driven social media
data from four cities (Paris, Milan, New York, and London) during the 2019 Fall/Winter (F/W) …
data from four cities (Paris, Milan, New York, and London) during the 2019 Fall/Winter (F/W) …
Fashion trend forecasting using machine learning techniques: a review
AA Chang, Cynthia, Devita, JF Ramadhan… - Data Science and …, 2021 - Springer
Fashion is a fast-paced industry where patterns last up to eight months, being an incredibly
competitive industry where trends are constantly evolving. When it comes to companies …
competitive industry where trends are constantly evolving. When it comes to companies …
fashion after fashion: A report of ai in fashion
X Zou, W Wong - arXiv preprint arXiv:2105.03050, 2021 - arxiv.org
In this independent report fAshIon after fashion, we examine the development of fAshIon
(artificial intelligence (AI) in fashion) and explore its potentiality to become a major disruptor …
(artificial intelligence (AI) in fashion) and explore its potentiality to become a major disruptor …
Explainable AI based interventions for pre-season decision making in fashion retail
Future of sustainable fashion lies in adoption of AI for a better understanding of consumer
shopping behaviour and using this understanding to further optimize product design …
shopping behaviour and using this understanding to further optimize product design …
Predicting best-selling new products in a major promotion campaign through graph convolutional networks
Many e-commerce platforms, such as AliExpress, run major promotion campaigns regularly.
Before such a promotion, it is important to predict potential best sellers and their respective …
Before such a promotion, it is important to predict potential best sellers and their respective …