论文标题
带有文本和图像的在线二手项目的价格建议
Price Suggestion for Online Second-hand Items with Texts and Images
论文作者
论文摘要
本文根据上传的图像和文本说明提供了一个智能的价格建议系统，用于在线二手列表。价格预测的目的是帮助卖家将其二手物品的有效和合理的价格设置为图像和文本说明上传到在线平台上。具体来说，我们设计了一个多模式的价格建议系统，该系统将提取的视觉和文本功能以及一些从二手项目购物平台收集的统计项目功能以及一些二进制二手项目的图像和文本是否有资格使用二进制分类模型来确定合理的价格建议，并提供与合格的图像和文本遗产模型一起提供的二边形项目。为了满足不同的需求，将两个不同的约束添加到分类模型和回归模型的联合培训中。此外，定制损失功能旨在优化回归模型，以提供二手项目的价格建议，这不仅可以最大程度地提高卖方的收益，而且还可以促进在线交易。我们还得出了一组指标，以更好地评估建议的价格建议系统。大型现实世界数据集的广泛实验证明了拟议的多模式价格建议系统的有效性。
This paper presents an intelligent price suggestion system for online second-hand listings based on their uploaded images and text descriptions. The goal of price prediction is to help sellers set effective and reasonable prices for their second-hand items with the images and text descriptions uploaded to the online platforms. Specifically, we design a multi-modal price suggestion system which takes as input the extracted visual and textual features along with some statistical item features collected from the second-hand item shopping platform to determine whether the image and text of an uploaded second-hand item are qualified for reasonable price suggestion with a binary classification model, and provide price suggestions for second-hand items with qualified images and text descriptions with a regression model. To satisfy different demands, two different constraints are added into the joint training of the classification model and the regression model. Moreover, a customized loss function is designed for optimizing the regression model to provide price suggestions for second-hand items, which can not only maximize the gain of the sellers but also facilitate the online transaction. We also derive a set of metrics to better evaluate the proposed price suggestion system. Extensive experiments on a large real-world dataset demonstrate the effectiveness of the proposed multi-modal price suggestion system.
