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Semantic Models for the First-Stage Retrieval: A Comprehensive Review

文献类型：期刊论文

作者Guo, Jiafeng1,2; Cai, Yinqiong1,2; Fan, Yixing1,2; Sun, Fei3; Zhang, Ruqing1,2; Cheng, Xueqi1,2
刊名ACM TRANSACTIONS ON INFORMATION SYSTEMS
出版日期2022-10-01
卷号40期号:4页码:42
关键词Semantic retrieval models information retrieval survey
ISSN号1046-8188
DOI10.1145/3486250
英文摘要Multi-stage ranking pipelines have been a practical solution in modern search systems, where the first-stage retrieval is to return a subset of candidate documents and latter stages attempt to re-rank those candidates. Unlike re-ranking stages going through quick technique shifts over the past decades, the first-stage retrieval has long been dominated by classical term-based models. Unfortunately, these models suffer from the vocabulary mismatch problem, which may block re-ranking stages from relevant documents at the very beginning. Therefore, it has been a long-term desire to build semantic models for the first-stage retrieval that can achieve high recall efficiently. Recently, we have witnessed an explosive growth of research interests on the first-stage semantic retrieval models. We believe it is the right time to survey current status, learn from existing methods, and gain some insights for future development. In this article, we describe the current landscape of the first-stage retrieval models under a unified framework to clarify the connection between classical term-based retrieval methods, early semantic retrieval methods, and neural semantic retrieval methods. Moreover, we identify some open challenges and envision some future directions, with the hope of inspiring more research on these important yet less investigated topics.
资助项目Beijing Academy of Artificial Intelligence (BAAI)[BAAI2019ZD0306] ; National Natural Science Foundation of China (NSFC)[61902381] ; National Natural Science Foundation of China (NSFC)[62006218] ; National Natural Science Foundation of China (NSFC)[61872338] ; Youth Innovation Promotion Association CAS[20144310] ; Youth Innovation Promotion Association CAS[2021100] ; Lenovo-CAS Joint Lab Youth Scientist Project ; Foundation and Frontier Research Key Program of Chongqing Science and Technology Commission[cstc2017jcyjBX0059]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000796738200003
出版者ASSOC COMPUTING MACHINERY
源URL[http://119.78.100.204/handle/2XEOYT63/19566]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Fan, Yixing
作者单位1.Univ Chinese Acad Sci, 6 Kexueyuan South Rd, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, CAS Key Lab Network Data Sci & Technol, Beijing, Peoples R China
3.Alibaba Grp, Beijing 100102, Peoples R China
推荐引用方式
GB/T 7714		 Guo, Jiafeng,Cai, Yinqiong,Fan, Yixing,et al. Semantic Models for the First-Stage Retrieval: A Comprehensive Review[J]. ACM TRANSACTIONS ON INFORMATION SYSTEMS,2022,40(4):42.
APA Guo, Jiafeng,Cai, Yinqiong,Fan, Yixing,Sun, Fei,Zhang, Ruqing,&Cheng, Xueqi.(2022).Semantic Models for the First-Stage Retrieval: A Comprehensive Review.ACM TRANSACTIONS ON INFORMATION SYSTEMS,40(4),42.
MLA Guo, Jiafeng,et al."Semantic Models for the First-Stage Retrieval: A Comprehensive Review".ACM TRANSACTIONS ON INFORMATION SYSTEMS 40.4(2022):42.

入库方式： OAI收割

来源：计算技术研究所

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