电子商务中的信息发现

IF 8.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Foundations and Trends in Information Retrieval Pub Date : 2024-12-30 DOI:10.1561/1500000097
Zhaochun Ren, Xiangnan He, Dawei Yin, Maarten de Rijke
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引用次数: 0

摘要

电子商务,或电子商务,是商品和服务的买卖,或在线传输资金或数据。电子商务平台种类繁多,有亚马逊、Airbnb、阿里巴巴、Booking.com、eBay和京东等全球企业,也有Bol.com和Flipkart.com等针对特定地理区域的平台。信息检索在电子商务中发挥着天然的作用,特别是在将人与商品和服务联系起来的过程中。电子商务中的信息发现涉及不同类型的搜索(例如,探索性搜索与查找任务)、推荐系统和电子商务门户中的自然语言处理。电子商务网站的普及使得电子商务中的信息发现研究日益活跃。这一领域的出版物和专门讲习班的增加证明了这一点。电子商务中的信息发现方法主要集中在提高电子商务搜索和推荐系统的有效性,丰富和使用知识图来支持电子商务,以及开发创新的问答和基于机器人的解决方案,帮助将人与商品和服务联系起来。在本调查中,概述了电子商务中信息发现的基本基础设施、算法和技术解决方案。涵盖的主题包括电子商务中的用户行为和分析、搜索、推荐和语言技术。
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Information Discovery in E-commerce

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, Booking.com, eBay, and JD.com and platforms targeting specific geographic regions such as Bol.com and Flipkart.com. 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.

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来源期刊
Foundations and Trends in Information Retrieval
Foundations and Trends in Information Retrieval COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
39.10
自引率
0.00%
发文量
3
期刊介绍: The surge in research across all domains in the past decade has resulted in a plethora of new publications, causing an exponential growth in published research. Navigating through this extensive literature and staying current has become a time-consuming challenge. While electronic publishing provides instant access to more articles than ever, discerning the essential ones for a comprehensive understanding of any topic remains an issue. To tackle this, Foundations and Trends® in Information Retrieval - FnTIR - addresses the problem by publishing high-quality survey and tutorial monographs in the field. Each issue of Foundations and Trends® in Information Retrieval - FnT IR features a 50-100 page monograph authored by research leaders, covering tutorial subjects, research retrospectives, and survey papers that provide state-of-the-art reviews within the scope of the journal.
期刊最新文献
Mathematical Information Retrieval: Search and Question Answering Information Discovery in E-commerce Fairness in Search Systems Multi-hop Question Answering User Simulation for Evaluating Information Access Systems
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