查询推荐研究综述  

A Review of Query Suggestion

作　　者：张晓娟[1] 彭琳 李倩[3] Zhang Xiaojuan;Peng Lin;Li Qian(School of Computer and Information Science,Southwest University,Chongqing 400715;National Science Library,Chinese Academy of Sciences,Beijing 100190;School of Economics and Management,Shanxi University,Taiyuan 030006)

机构地区：[1]西南大学计算机与信息科学学院,重庆400715 [2]中国科学院文献情报中心,北京100190 [3]山西大学经济与管理学院,太原030006

出　　处：《情报学报》2019年第4期432-446,共15页Journal of the China Society for Scientific and Technical Information

基　　金：国家社会科学基金青年项目"融合用户个性化与实时性意图的查询推荐模型研究"(15CTQ019)

摘　　要：查询推荐是一种提高用户搜索效率的重要技术,其核心任务是帮助用户构造有效查询并以此准确描述用户信息需求。作为当今搜索引擎的核心技术之一,查询推荐吸引了学术界和工业界的广泛关注,一直以来都是信息检索领域中重要的研究主题。本文以国内外会议、期刊发表的有关查询推荐研究的文献为对象,利用归纳总结方法,首先详细梳理了查询推荐中主流方法——基于简单共现信息的方法、基于图模型的方法以及融合多种信息的方法,然后总结评述了评测方法与指标,最后分析了未来可能的研究方向。Query suggestion is an important technique for improving search efficiency,and its core task is to help users construct effective queries to accurately describe users'information requirements.As a core technology of search engines,query suggestion has attracted wide attention in both academia and industry and has long been considered to be an important research topic in information retrieval.This paper summarizes the recent research progress in query suggestion using papers published in China's and international conferences and journals.On this basis,the mainstream methods-simple occurrence information-based method,graph-based method,and integration of multiple information-based methods-are reviewed in detail in this paper.Then,the related evaluation methods and metrics are summarized and discussed.Finally,the possible future research directions are pointed out.

关 键 词：查询推荐 查询 用户意图 查询会话 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]