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2017 | OriginalPaper | Chapter

i-Stylist: Finding the Right Dress Through Your Social Networks

Authors : Jordi Sanchez-Riera, Jun-Ming Lin, Kai-Lung Hua, Wen-Huang Cheng, Arvin Wen Tsui

Published in: MultiMedia Modeling

Publisher: Springer International Publishing

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Abstract

Searching the Web has become an everyday task for most people. However, the presence of too much information can cause information overload. For example, when shopping online, a user can easily be overwhelmed by too many choices. To this end, we propose a personalized clothing recommendation system, namely i-Stylist, through the analysis of personal images in social networks. To access the available personal images of a user, the i-Stylist system extracts a number of characteristics from each clothing item such as CNN feature vectors and metadata such as color, material and pattern of the fabric. Then, these clothing items are organized as a fully connected graph to later infer the personalized probability distribution of how the user will like each clothing item in a shopping website. The user is able to modify the graph structure, e.g. adding and deleting vertices by giving feedback about the retrieved clothing items. The i-Stylist system is compared against two other baselines and demonstrated to have better performance.

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Footnotes
1
Usually a popular item is defined by the number of likes, links, etc., that an image or user can have.
 
3
Different from the authors of this paper.
 
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Metadata
Title
i-Stylist: Finding the Right Dress Through Your Social Networks
Authors
Jordi Sanchez-Riera
Jun-Ming Lin
Kai-Lung Hua
Wen-Huang Cheng
Arvin Wen Tsui
Copyright Year
2017
Book
MultiMedia Modeling

Print ISBN: 978-3-319-51810-7

Electronic ISBN: 978-3-319-51811-4

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-51811-4_54