arXiv:2410.05763cs.IRcs.CL2024-10被引 15

综述电商信息发现关键技术,涵盖搜索、推荐与语言处理。

Information Discovery in e-Commerce

  • 系统梳理电商信息发现的基础设施与核心技术
  • 覆盖用户行为建模、搜索推荐与自然语言处理技术
  • 适合对电商算法研究者或产品经理参考

电子商业(e-commerce)是通过网络购买和销售商品和服务,或传输资金或数据。电商平台种类繁多,包括亚马逊、爱彼迎、阿里巴巴、易贝等全球平台,以及针对特定地理区域的平台。信息检索在电商中具有天然作用,尤其在连接用户与商品服务方面。电商中的信息发现涉及多种搜索形式(如探索性搜索与查找任务)、推荐系统及电商平台中的自然语言处理。随着电商平台普及,该领域的研究日益活跃,体现在论文数量增长和相关研讨会增多。信息发现方法主要聚焦于提升电商搜索与推荐系统的有效性,利用知识图谱丰富和增强信息支持,开发创新的问答系统与机器人解决方案,以更好连接用户与商品服务。本文综述了电商信息发现的基础架构、算法与技术方案,涵盖用户行为与画像、搜索、推荐及电商中的语言技术。

原文摘要 · Abstract (English)

Electronic commerce, or e-commerce, is the buying and selling of goods and services, or the transmitting of funds or data online. E-commerce platforms come in many kinds, with global players such as Amazon, Airbnb, Alibaba, eBay and platforms targeting specific geographic regions. Information retrieval has a natural role to play in e-commerce, especially in connecting people to goods and services. Information discovery in e-commerce concerns different types of search (e.g., exploratory search vs. lookup tasks), recommender systems, and natural language processing in e-commerce portals. The rise in popularity of e-commerce sites has made research on information discovery in e-commerce an increasingly active research area. This is witnessed by an increase in publications and dedicated workshops in this space. Methods for information discovery in e-commerce largely focus on improving the effectiveness of e-commerce search and recommender systems, on enriching and using knowledge graphs to support e-commerce, and on developing innovative question answering and bot-based solutions that help to connect people to goods and services. In this survey, an overview is given of the fundamental infrastructure, algorithms, and technical solutions for information discovery in e-commerce. The topics covered include user behavior and profiling, search, recommendation, and language technology in e-commerce.

电商搜索推荐系统语言技术知识图谱

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