A Visual Similarity Recommendation System using Generative Adversarial Networks

Betul Ay, G. Aydin, Zeynep Koyun, Mehmet Demir
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引用次数: 16

Abstract

The goal of content-based recommendation system is to retrieve and rank the list of items that are closest to the query item. Today, almost every e-commerce platform has a recommendation system strategy for products that customers can decide to buy. In this paper we describe our work on creating a Generative Adversarial Network based image retrieval system for e-commerce platforms to retrieve best similar images for a given product image specifically for shoes. We compare state-of-the-art solutions and provide results for the proposed deep learning network on a standard data set.
基于生成对抗网络的视觉相似性推荐系统
基于内容的推荐系统的目标是检索最接近查询项的项目列表并对其进行排序。今天,几乎每个电子商务平台都有一个产品推荐系统策略,客户可以决定购买。在本文中,我们描述了我们为电子商务平台创建基于生成对抗网络的图像检索系统的工作,以检索特定产品图像的最佳相似图像,特别是鞋子。我们比较了最先进的解决方案,并在标准数据集上为提出的深度学习网络提供了结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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