How users select query suggestions under different satisfaction states?

Zhenguo Shang; Jingfei Li; Peng Zhang; Dawei Song; Benyou Wang

doi:10.1007/978-3-319-68699-8_8

How users select query suggestions under different satisfaction states?

Zhenguo Shang
, Jingfei Li
, Peng Zhang^*
, Dawei Song
, Benyou Wang

^*此作品的通讯作者

Tianjin University
Open University Milton Keynes

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

Query suggestion (or recommendation) has become an important technique in commercial search engines (e.g., Google, Bing and Baidu) in order to improve users’ search experience. Most existing studies on query suggestion focus on formalizing various query suggestion models, while ignoring the study on investigating how users select query suggestions under different satisfaction states. Specifically, although a number of effective query suggestion models have been proposed, some basic problems have not been well investigated. For example, (i) how much the importance of query suggestion feature for users with respect to different queries; (ii) how user’s satisfaction for current search results will influence the selection of query suggestions. In this paper, we conduct extensive user study with a search engine interface in order to investigate above problems. Through the user study, we gain a series of insightful findings which may benefit for the design of future search engine and query suggestion models.

源语言	英语
主期刊名	Information Retrieval - 23rd China conference, CCIR 2017, Proceedings
编辑	Jianyun Nie, Tong Ruan, Tieyun Qian, Jirong Wen, Yiqun Liu
出版商	Springer Verlag
页	93-105
页数	13
ISBN（印刷版）	9783319686981
DOI	https://doi.org/10.1007/978-3-319-68699-8_8
出版状态	已出版 - 2017
已对外发布	是
活动	23rd China conference on Information Retrieval, CCIR 2017 - Shanghai, 中国期限: 13 7月 2017 → 14 7月 2017

丛书

姓名	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	10390 LNCS
ISSN（印刷版）	0302-9743
ISSN（电子版）	1611-3349

会议

会议	23rd China conference on Information Retrieval, CCIR 2017
国家/地区	中国
市	Shanghai
时期	13/07/17 → 14/07/17

访问文件

10.1007/978-3-319-68699-8_8

其它文件与链接

链接到 Scopus 的出版物

引用此

Shang, Z., Li, J., Zhang, P., Song, D., & Wang, B. (2017). How users select query suggestions under different satisfaction states? 在 J. Nie, T. Ruan, T. Qian, J. Wen, & Y. Liu (版本), Information Retrieval - 23rd China conference, CCIR 2017, Proceedings (页码 93-105). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 10390 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-68699-8_8

Shang, Zhenguo ; Li, Jingfei ; Zhang, Peng 等. / How users select query suggestions under different satisfaction states?. Information Retrieval - 23rd China conference, CCIR 2017, Proceedings. 编辑 / Jianyun Nie ; Tong Ruan ; Tieyun Qian ; Jirong Wen ; Yiqun Liu. Springer Verlag, 2017. 页码 93-105 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{6296f6cd6ffa4197bfea2fa9f775bbf6,

title = "How users select query suggestions under different satisfaction states?",

abstract = "Query suggestion (or recommendation) has become an important technique in commercial search engines (e.g., Google, Bing and Baidu) in order to improve users{\textquoteright} search experience. Most existing studies on query suggestion focus on formalizing various query suggestion models, while ignoring the study on investigating how users select query suggestions under different satisfaction states. Specifically, although a number of effective query suggestion models have been proposed, some basic problems have not been well investigated. For example, (i) how much the importance of query suggestion feature for users with respect to different queries; (ii) how user{\textquoteright}s satisfaction for current search results will influence the selection of query suggestions. In this paper, we conduct extensive user study with a search engine interface in order to investigate above problems. Through the user study, we gain a series of insightful findings which may benefit for the design of future search engine and query suggestion models.",

keywords = "Eye tracking, Novelty, Query suggestion, User satisfaction, User study",

author = "Zhenguo Shang and Jingfei Li and Peng Zhang and Dawei Song and Benyou Wang",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 23rd China conference on Information Retrieval, CCIR 2017 ; Conference date: 13-07-2017 Through 14-07-2017",

year = "2017",

doi = "10.1007/978-3-319-68699-8\_8",

language = "English",

isbn = "9783319686981",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "93--105",

editor = "Jianyun Nie and Tong Ruan and Tieyun Qian and Jirong Wen and Yiqun Liu",

booktitle = "Information Retrieval - 23rd China conference, CCIR 2017, Proceedings",

address = "Germany",

}

Shang, Z, Li, J, Zhang, P, Song, D & Wang, B 2017, How users select query suggestions under different satisfaction states? 在 J Nie, T Ruan, T Qian, J Wen & Y Liu (版本), Information Retrieval - 23rd China conference, CCIR 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 10390 LNCS, Springer Verlag, 页码 93-105, 23rd China conference on Information Retrieval, CCIR 2017, Shanghai, 中国, 13/07/17. https://doi.org/10.1007/978-3-319-68699-8_8

How users select query suggestions under different satisfaction states? / Shang, Zhenguo; Li, Jingfei; Zhang, Peng 等.
Information Retrieval - 23rd China conference, CCIR 2017, Proceedings. 编辑 / Jianyun Nie; Tong Ruan; Tieyun Qian; Jirong Wen; Yiqun Liu. Springer Verlag, 2017. 页码 93-105 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 10390 LNCS).