報告題目：Fashion Informatics: Big Data in Fashion

報告時間：2018年5月29日下午14：45

報告地點：旭日樓306教室

主講人：Li Zhao博士

主講人簡介

Dr. Zhao is an Assistant Professor at the University of Missouri in the Textile and Apparel Management Department. Her teaching experience is dynamic in not only course content but also cultural diversity. She has taught courses in China and the United States in Product Development, Luxury Fashion Markets and Global Consumers. She utilizes her experience and interaction with students to integrate real-world situations and challenges into the course content, projects and related assignments in order to better prepare students for their future careers. Dr. Zhao’s primary research interest is the entrepreneurial spirits in emerging technologies (big data and social network analysis, direct digital manufacturing), and sustainable development in the global textile and apparel supply chain. Her research can be categorized as interdisciplinary with aspects of textile and apparel management, informatics and data science, and business studies. She has published over thirty research papers in diverse international referred journals, book chapters and conferences for the said research domains.

報告簡介

Machine learning and knowledge discovery techniques have a long history of application to fields of practice such as marketing and business intelligence. Fashion and other manufacturing compartments have comparably enjoyed little attention from computer scientists. However, with the increasing availability of multimedia data from social media, conditions for a broad change in these areas are starting emerge. This lecture poses to expand apparel and textile professionals and academics regarding our understanding of the fashion apparel industry through the use of large scale datasets extracted from social media such as Twitter and Instagram. The type of investigation we envision can be regarded as unique and novel of disciplines that have seldom collaborated together before.  Tapping into thousands of designer runway comments and discussions, as well as millions of likes, comments, shares, tweets, pins, and Instagram posts about “what’s hot and what’s not,” a combination of theoretical, computational, and statistical approaches can be used to better understand the dynamic nature of fashion trends and fashion consumers. This new interdisciplinary field—fashion informatics—may help fashion companies come to startling conclusions about their designs and revolutionize the way industrialists and brands produce apparels and accessories.