[Objective] This paper studies the changes of queries from cross-device searching, aiming to improve users’ experience. [Methods] With the help of user experiment, log analysis and cluster analysis, we examined the cross-device search queries for their length, diversity, and the number of keywords, as well as the changing of their semantic similarities. [Results] The length and the keyword numbers of queries from desktop devices were much higher than those from the mobile devices. However, the diversities of queries did not make significant changes. There were W, M, and V patterns for semantic similarities among cross-device search queries. [Limitations] The number of experiment participants needs to be increased, which could generate more queries for future studies. [Conclusions] The changing patterns of query semantic similarities reflects users’ searching strategies, which benefits cross-device searching services.
(Wu Dan, Liang Shaobo, Ran Aihua.Mobile Search Strategies of College Students[J]. Journal of Library Science in China, 2016, 42(3): 55-73.)
Guan D, Zhang S, Yang H.Utilizing Query Change for Session Search[C]// Proceedings of International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2013: 453-462.
Fu H.Query Reformulation Patterns of Mixed Language Queries in Different Search Intents[C]// Proceedings of the 2017 Conference on Human Information Interaction and Retrieval. ACM, 2017: 249-252.
Geronimo L D, Husmann M, Norrie M C.Surveying Personal Device Ecosystems with Cross-device Applications in Mind[C]// Proceedings of the 5th ACM International Symposium on Pervasive Displays. ACM, 2016: 220-227.
Sohn T, Battestini A, Horii H, et al.Supporting Unplanned Activities Through Cross-device Interaction[C]// Proceedings of International Conference on Automotive User Interfaces and Interactive Vehicular Applications. ACM, 2010: 146-147.
Sohn T, Mori K, Setlur V.Enabling Cross-device Interaction with Web History[C]// Proceedings of the 28th International Conference Extended Abstracts on Human Factors in Computing Systems. ACM, 2010: 3883-3888.
Han S, Yue Z, He D.Understanding and Supporting Cross-Device Web Search for Exploratory Tasks with Mobile Touch Interactions[J]. ACM Transactions on Information Systems, 2015, 33(4): 1-34.
Kotov A, Bennett P N, White R W, et al.Modeling and Analysis of Cross-session Search Tasks[C]// Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2011: 5-14.
Yue Z, Han S, He D.An investigation of the Query Behavior in Task-based Collaborative Exploratory Web Search[J]. Proceedings of the American Society for Information Science & Technology, 2014, 50(1): 1-10.
Liu Bing.Web数据挖掘[M]. 北京: 清华大学出版社, 2009:247.
(Liu Bing.Web Data Mining[M]. Beijing: Tsinghua University Press, 2009: 247.)
Han J, Kamber M, Pei J.数据挖掘: 概念与技术[M]. 第3版. 范明, 孟小峰译. 北京: 机械工业出版社, 2012: 77-78.
(Han J, Kamber M, Pei J.Data Mining: Concepts and Techniques [M]. The 3rd Edition. Translated by Fan Ming, Meng Xiaofeng. Beijing: China Machine Press, 2012: 77-78.)
Liu C, Liu J, Belkin N J.Predicting Search Task Difficulty at Different Search Stages[C]// Proceedings of the ACM International Conference on Information and Knowledge Management. ACM, 2014: 569-578.
Wu D, Yao X, Dong J, et al.Designing Mobile Search Tasks: A Context-Based Approach[J]. Geomatics and Information Science of Wuhan University, 2016, 41(S): 34-39.
Kamvar M, Kellar M, Patel R, et al.Computers and iPhones and Mobile Phones, oh My!: A Logs-based Comparison of Search Users on Different Devices[C]// Proceedings of International Conference on World Wide Web. ACM, 2009: 801-810.