I-stylist: Finding the right dress through your social networks
Journal
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Journal Volume
10132 LNCS
ISBN
9783319518107
Date Issued
2017-01-01
Author(s)
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.
Subjects
Clothing items | Convolutional neural networks (CNN) | Dress style | Personalized recommendation | Social network
Type
conference paper