Fad2vec: 판매 데이터 임베딩 기반 패션 산업 단발성 유행 탐지

Translated title of the contribution: Fad2Vec: Detecting Fads in the Fashion Industry Based on Sales Embedding

Research output: Contribution to journalArticlepeer-review

Abstract

In the fashion industry, fads, a phenomenon in which demand for specific items surges in a short time and then disappears, are often observed. However, the conventional demand forecasting methods have limitations in predicting fads because it focuses on long-term trends. This paper presents a new approach called Fad2Vec, which adapts the Item2Vec approach to detect fads effectively. Hot periods composed of a hot point and a preceding period for each product are identified based on time-series sales data. Products are embedded into vectors representing the time points when they are temporarily fashionable. Then, they are clustered into a fad group where fashion items belong to the same cluster and show similar fad patterns. A case study of four famous fashion brands is provided to show how Fad2Vec works and verify its validity. The proposed Fad2Vec approach is expected to be practically utilized for the production planning of fast fashion companies.
Translated title of the contributionFad2Vec: Detecting Fads in the Fashion Industry Based on Sales Embedding
Original languageKorean
Pages (from-to)249-258
Number of pages10
Journal대한산업공학회지
Volume48
Issue number2
DOIs
StatePublished - Apr 2022

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