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Artificial Intelligence for Fashion Industry in the Big Data Era

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Cover of 'Artificial Intelligence for Fashion Industry in the Big Data Era'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction: Artificial Intelligence for Fashion Industry in the Big Data Era
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    Chapter 2 AI-Based Fashion Sales Forecasting Methods in Big Data Era
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    Chapter 3 Enhanced Predictive Models for Purchasing in the Fashion Field by Applying Regression Trees Equipped with Ordinal Logistic Regression
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    Chapter 4 A Data Mining-Based Framework for Multi-item Markdown Optimization
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    Chapter 5 Social Media Analytics for Decision Support in Fashion Buying Processes
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    Chapter 6 Review of Artificial Intelligence Applications in Garment Manufacturing
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    Chapter 7 AI for Apparel Manufacturing in Big Data Era: A Focus on Cutting and Sewing
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    Chapter 8 A Discrete Event Simulation Model with Genetic Algorithm Optimisation for Customised Textile Production Scheduling
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    Chapter 9 An Intelligent Fashion Replenishment System Based on Data Analytics and Expert Judgment
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    Chapter 10 Blockchain-Based Secured Traceability System for Textile and Clothing Supply Chain
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    Chapter 11 Artificial Intelligence Applied to Multisensory Studies of Textile Products
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    Chapter 12 Evaluation of Fashion Design Using Artificial Intelligence Tools
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    Chapter 13 Garment Wearing Comfort Analysis Using Data Mining Technology
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    Chapter 14 Garment Fit Evaluation Using Machine Learning Technology
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Title
Artificial Intelligence for Fashion Industry in the Big Data Era
Published by
Springer Singapore, July 2018
DOI 10.1007/978-981-13-0080-6
ISBNs
978-9-81-130079-0, 978-9-81-130080-6
Editors

Thomassey, Sébastien, Zeng, Xianyi

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Postgraduate 1 100%
Unspecified 1 100%
Readers by discipline Count As %
Unspecified 1 100%
Materials Science 1 100%