Visually-Aware Personalized Recommendation using Interpretable Image Representations

by   Charles Packer, et al.
University of California, San Diego

Visually-aware recommender systems use visual signals present in the underlying data to model the visual characteristics of items and users' preferences towards them. In the domain of clothing recommendation, incorporating items' visual information (e.g., product images) is particularly important since clothing item appearance is often a critical factor in influencing the user's purchasing decisions. Current state-of-the-art visually-aware recommender systems utilize image features extracted from pre-trained deep convolutional neural networks, however these extremely high-dimensional representations are difficult to interpret, especially in relation to the relatively low number of visual properties that may guide users' decisions. In this paper we propose a novel approach to personalized clothing recommendation that models the dynamics of individual users' visual preferences. By using interpretable image representations generated with a unique feature learning process, our model learns to explain users' prior feedback in terms of their affinity towards specific visual attributes and styles. Our approach achieves state-of-the-art performance on personalized ranking tasks, and the incorporation of interpretable visual features allows for powerful model introspection, which we demonstrate by using an interactive recommendation algorithm and visualizing the rise and fall of fashion trends over time.


page 1

page 2

page 3

page 4


Visually-aware Recommendation with Aesthetic Features

Visual information plays a critical role in human decision-making proces...

VBPR: Visual Bayesian Personalized Ranking from Implicit Feedback

Modern recommender systems model people and items by discovering or `tea...

Visually-Aware Fashion Recommendation and Design with Generative Image Models

Building effective recommender systems for domains like fashion is chall...

Vista: A Visually, Socially, and Temporally-aware Model for Artistic Recommendation

Understanding users' interactions with highly subjective content---like ...

CuratorNet: Visually-aware Recommendation of Art Images

Although there are several visually-aware recommendation models in domai...

Aesthetic-based Clothing Recommendation

Recently, product images have gained increasing attention in clothing re...

Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filtering

Building a successful recommender system depends on understanding both t...

Please sign up or login with your details

Forgot password? Click here to reset