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 …

Sales forecasting during the launch of new products has always been a challenging task,
due to the lack of historical sales data. The dynamic market environment and consumer …

For fashion outfits to be considered aesthetically pleasing, the garments that constitute them
need to be compatible in terms of visual aspects, such as style, category and color. Previous …

Abstract We present Visuelle 2.0, the first dataset useful for facing diverse prediction
problems that a fast-fashion company has to manage routinely. Furthermore, we …

Understanding consumer preference is crucial for optimizing inventory management and
enhancing consumer satisfaction. While previous research has explored various …

We propose a data-centric pipeline able to generate exogenous observation data for the
New Fashion Product Performance Forecasting (NFPPF) problem, ie, predicting the …

Reviews left by consumers on e-commerce platforms provide crucial marketing information
as they are a publicly available source of information providing insight into consumers' …

New product sales prediction is crucial for the digital economy as it enables businesses to
make informed decisions about product development, inventory management, marketing …

Fashion trend forecasting has consistently remained a focal point within the realm of fashion.
Existing methods predominantly concentrate on the external factors influencing fashion …

Predicting future sales volumes of fashion industry products is challenging due to rapid
market changes and limited historical sales data for recent products. As traditional …