Graph convolution networks (GCN), which recently becomes new state-of-the-art method for graph node classification, recommendation and other applications, has not been successfully applied to industrial-scale search engine yet. In this proposal, we introduce our approach, namely SearchGCN, for embedding-based candidate retrieval in one of the largest e-commerce search engine in the world. Empirical studies demonstrate that SearchGCN learns better embedding representations than existing methods, especially for long tail queries and items. Thus, SearchGCN has been deployed into JD.com's search production since July 2020.

中文翻译：

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SearchGCN：通过图卷积网络为电子商务搜索提供嵌入检索的支持

图卷积网络（GCN）最近成为图节点分类、推荐和其他应用的最先进的新方法，但尚未成功应用于工业规模的搜索引擎。在本提案中，我们介绍了我们的方法，即 SearchGCN，用于在世界上最大的电子商务搜索引擎之一中进行基于嵌入的候选检索。实证研究表明，SearchGCN 比现有方法学习更好的嵌入表示，尤其是对于长尾查询和项目。因此，自 2020 年 7 月起，SearchGCN 已部署到京东的搜索产品中。