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运营电子商务搜索级联排名

Cascade Ranking for Operational Ecommerce Search
课程网址: http://videolectures.net/kdd2017_liu_cascade_ranking/  
主讲教师: 刘世臣
开课单位: 阿里巴巴集团
开课时间: 2017-10-09
课程语种: 英语
中文简介:
在“大数据”时代,许多现实世界的应用程序(例如搜索)都涉及大量项目的排名问题。获得有效的排名结果,同时及时高效地获得结果对于提供良好的用户体验和节省计算成本非常重要。为了学习有效排名,例如级联排名(学习)模型,已经进行了有价值的先前研究,该模型使用一系列排名函数来逐步过滤某些项目并对剩余项目进行排名。然而,大多数现有的学习在搜索中有效排名的研究都是在相对较小的计算环境中通过模拟用户查询进行研究的。本文介绍了在大规模运营电子商务搜索应用程序 (CLOES) 中设计和部署级联模型的新颖研究和深入研究,该应用程序每天使用数百台服务器处理数亿用户查询。现实世界应用的挑战为研究提供了新的见解:1)。现实世界的搜索应用程序通常涉及用户体验和计算成本方面的多个偏好或约束因素,例如搜索准确性、搜索延迟、搜索结果大小和总 CPU 成本,而大多数现有搜索解决方案仅解决一两个因素;2)。电子商务搜索的有效性涉及点击、购买等多种类型的用户行为,而现有的大多数搜索级联排序仅对点击行为进行建模。根据这些观察,设计了一种新颖的级联排名模型并将其部署在可操作的电子商务搜索应用程序中。大量的实验证明了所提出的工作在解决实际应用中的有效性、效率和用户体验的多个因素方面的优势。
课程简介: In the 'Big Data' era, many real-world applications like search involve the ranking problem for a large number of items. It is important to obtain effective ranking results and at the same time obtain the results efficiently in a timely manner for providing good user experience and saving computational costs. Valuable prior research has been conducted for learning to efficiently rank like the cascade ranking (learning) model, which uses a sequence of ranking functions to progressively filter some items and rank the remaining items. However, most existing research of learning to efficiently rank in search is studied in a relatively small computing environments with simulated user queries. This paper presents novel research and thorough study of designing and deploying a Cascade model in a Large-scale Operational E-commerce Search application (CLOES), which deals with hundreds of millions of user queries per day with hundreds of servers. The challenge of the real-world application provides new insights for research: 1). Real-world search applications often involve multiple factors of preferences or constraints with respect to user experience and computational costs such as search accuracy, search latency, size of search results and total CPU cost, while most existing search solutions only address one or two factors; 2). Effectiveness of e-commerce search involves multiple types of user behaviors such as click and purchase, while most existing cascade ranking in search only models the click behavior. Based on these observations, a novel cascade ranking model is designed and deployed in an operational e-commerce search application. An extensive set of experiments demonstrate the advantage of the proposed work to address multiple factors of effectiveness, efficiency and user experience in the real-world application.
关 键 词: 电子商务; 级联排名模型; 数据科学
课程来源: 视频讲座网
数据采集: 2023-12-25:wujk
最后编审: 2023-12-25:wujk
阅读次数: 10