交互式信息检索研究中的眼动追踪分析
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摘要
眼动追踪技术在信息检索领域的应用研究较为广泛,对该技术进行分析可以更加深入地理解信息搜索背后的行为动机。交互式信息检索研究中常用的眼动设备分为远程眼动仪、头戴式眼动仪和开源资源三种类型,常用的眼动指标有功能识别指标和情感识别指标,眼动分析方法常与其他方法结合使用,主要有Eye-Mouse协同模式、Eye-NP协同模式和Eye-Cognition协同模式,眼动追踪方法主要用于信息搜索行为影响因素研究,以及搜索引擎结果页面上的浏览行为、隐性相关反馈和预测推荐研究。基于上述发现,本研究构建了基于眼动的交互式信息检索模型,并提出眼动追踪在交互式信息检索研究中的四个应用趋势,包括:交互式信息检索中的认知差异研究;基于眼动的移动搜索研究;自然环境下的交互信息检索行为眼动研究;眼动追踪方法与其他多元化的分析方法的结合。
Eye-tracking was first used in the study of reading behavior,and with the development of this technology,it has been widely used in psychology,medicine,advertising,human-computer interaction and other fields.At present,the application of eye-tracking technology in the field of information retrieval is also a frontier topic. Interactive Information Retrieval( IIR) has a strong interdisciplinary nature,involving psychology,sociology,computer science and other fields. It is beneficial to use eye-tracking technology to better understand the motivation and mechanism of information seeking behavior. Although some studies have sorted out the application of eye tracking technology in the field of Library and Information Science,they have not yet elaborated the application of eye tracking technology in IIR and these studies only pointed out a general overview of eye tracking measurement indicators and the combination of eye tracking and other methods. The purpose of this paper is to expound the application of eye tracking technology in IIR as comprehensively as possible,and put forward the prospect of the research trends of eye tracking technologyin IIR.The literatures used in this paper mainly come from databases such as Wo S,ACM,Springer,Elsevier,Emerald,IEEE and CNKI. All of the selected literatures are closely related to IIR,the main method of which is eye-tracking. The retrieval methods of English documents are( "interactive information retrieval"or"information retrieval"or "information search behavior"or "information seeking behavior"or "web search") *( "eye-tracking"),and Chinese documents are( "交互式信息检索"OR"信息检索行为"OR"信息搜索行为"OR"信息搜寻行为"OR"网页搜索行为").Through reviewing the related researches,four findings can be concluded: 1) Eye-tracking devices used in the research of IIR can be divided into three types: remote eye-tracker,head-mounted eye-tracker and open resources; 2) Eye-tracking analysis indicators commonly used in IIR research can be divided into two categories: functional identification indicators( i. e. indicators inferring that stimulate materials can be noticed,found and recognized by the subjects) and emotional identification indicators( i.e. indicators that reflect the emotional and cognitive state of the subjects to stimulate); 3) Eye-tracking is often used in combination with other methods, including three patterns: Eye-mouse collaboration model, Eye-NP collaboration model and Eye-cognition collaboration model; 4) Four research topics about eye-tracking in IIR are identified: the factors that influence the information search behavior,the browsing behavior on SERP,implicit relevance feedback on SERP and the prediction and recommendation on SERP.Based on the findings above,an eye-tracking-based interactive information retrieval model is constructed.Meanwhile,three limitations of the current work are pointed out,including: there is a lack of in-depth study on the factors affecting IIR,such as individual characteristics,memory load and cognitive style and so on; most studies focus on the application of eye-tracking technology in desktop, lacking of the application in mobile; most eye-tracking studies are performed in the controlled laboratory,and there is a lack of IIR research performed in real environment. In view of the current limitations,we propose four research trends of eye-tracking research in IIR,including: cognitive difference research in IIR,mobile search behavior based on eye-tracking,IIR research in natural environment,and the combination of eyetracking and other research methods,especially neuropsychological methods.
Eye-tracking was first used in the study of reading behavior,and with the development of this technology,it has been widely used in psychology,medicine,advertising,human-computer interaction and other fields.At present,the application of eye-tracking technology in the field of information retrieval is also a frontier topic. Interactive Information Retrieval( IIR) has a strong interdisciplinary nature,involving psychology,sociology,computer science and other fields. It is beneficial to use eye-tracking technology to better understand the motivation and mechanism of information seeking behavior. Although some studies have sorted out the application of eye tracking technology in the field of Library and Information Science,they have not yet elaborated the application of eye tracking technology in IIR and these studies only pointed out a general overview of eye tracking measurement indicators and the combination of eye tracking and other methods. The purpose of this paper is to expound the application of eye tracking technology in IIR as comprehensively as possible,and put forward the prospect of the research trends of eye tracking technologyin IIR.The literatures used in this paper mainly come from databases such as Wo S,ACM,Springer,Elsevier,Emerald,IEEE and CNKI. All of the selected literatures are closely related to IIR,the main method of which is eye-tracking. The retrieval methods of English documents are( "interactive information retrieval"or"information retrieval"or "information search behavior"or "information seeking behavior"or "web search") *( "eye-tracking"),and Chinese documents are( "交互式信息检索"OR"信息检索行为"OR"信息搜索行为"OR"信息搜寻行为"OR"网页搜索行为").Through reviewing the related researches,four findings can be concluded: 1) Eye-tracking devices used in the research of IIR can be divided into three types: remote eye-tracker,head-mounted eye-tracker and open resources; 2) Eye-tracking analysis indicators commonly used in IIR research can be divided into two categories: functional identification indicators( i. e. indicators inferring that stimulate materials can be noticed,found and recognized by the subjects) and emotional identification indicators( i.e. indicators that reflect the emotional and cognitive state of the subjects to stimulate); 3) Eye-tracking is often used in combination with other methods, including three patterns: Eye-mouse collaboration model, Eye-NP collaboration model and Eye-cognition collaboration model; 4) Four research topics about eye-tracking in IIR are identified: the factors that influence the information search behavior,the browsing behavior on SERP,implicit relevance feedback on SERP and the prediction and recommendation on SERP.Based on the findings above,an eye-tracking-based interactive information retrieval model is constructed.Meanwhile,three limitations of the current work are pointed out,including: there is a lack of in-depth study on the factors affecting IIR,such as individual characteristics,memory load and cognitive style and so on; most studies focus on the application of eye-tracking technology in desktop, lacking of the application in mobile; most eye-tracking studies are performed in the controlled laboratory,and there is a lack of IIR research performed in real environment. In view of the current limitations,we propose four research trends of eye-tracking research in IIR,including: cognitive difference research in IIR,mobile search behavior based on eye-tracking,IIR research in natural environment,and the combination of eyetracking and other research methods,especially neuropsychological methods.
引文
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[3] Lund H. Eye tracking in Library and Information Science: a literature review[J]. Library Hi Tech, 2016, 34(4):585-614.
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[5] Rayner K. Eye movements in reading and information processing[J]. Psychological Bulletin, 1978, 85(3):618-660.
[6] Mostafa J, Gwizdka J. Deepening the role of the user: neuro-physiological evidence as a basis for studying and improving search[C]// ACM on Conference on Human Information Interaction and Retrieval. ACM, 2016:63-70.
[7] Lorigo L, Haridasan M, Brynjarsdóttir H, et al. Eye tracking and online search: lessons learned and challenges ahead[J]. Journal of the Association for Information Science & Technology, 2014, 59(7):1041-1052.
[8] Katti H, Kankanhalli M. Eye-tracking methodology and applications to images and video[C]// ACM International Conference on Multimedia. ACM, 2011:641-642.
[9] Papoutsaki A, Laskey J, Huang J. SearchGazer: Webcameye tracking for remote studies of web search[C]// Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval.AMC, 2017:17-26.
[10] Joachims T, Granka L, Pan B, et al. Accurately interpreting click through data as implicit feedback[J].ACM SIGIR Forum,2017,51(1):4-11.
[11] Joachims T, Granka L, Pan B, et al. Evaluating the accuracy of implicit feedback from clicks and query reformulations in web search[J]. Acm Transactions on Information Systems, 2007, 25(2):7.
[12] Vrochidis S, Patras I, Kompatsiaris I. An eye-tracking-based approach to facilitate interactive video search[C]// ACM International Conference on Multimedia Retrieval. ACM, 2011:1-8.
[13] Sari J N, Ferdiana R, Santosa P I, et al. An eye tracking study: exploration customer behavior on web design[C]// International Hci and Ux Conference in Indonesia. ACM, 2015:69-72.
[14] Chizari S. Exploring the role of culture in online searching behavior from cultural cognition perspective[C]// Proceedings of the 2016 ACM on Conference on Human Information Interaction and Retrieval. ACM, 2016:349-351.
[15] Marcos M C, Gavin F, Arapakis I. Effect of snippets on user experience in web search[C]// Proceedings of the XVI International Conference on Human Computer Interaction.ACM,2015:1-8.
[16] Kim J, Thomas P, Sankaranarayana R, et al. Comparing scanning behaviour in web search on small and large screens[C]// Seventeenth Australasian Document Computing Symposium, 2012:25-30.
[17] Rodden K, Fu X, Aula A, et al. Eye-mouse coordination patterns on web search results pages[C]// Extended Abstracts Proceedings of the 2008 Conference on Human Factors in Computing Systems, CHI 2008, Florence, Italy, April. DBLP, 2008:2997-3002.
[18] Liu Y, Wang C, Zhou K, et al. From skimming to reading: a two-stage examination model for web search[C]// Acm International Conference on Conference on Information & Knowledge Management. ACM, 2014:849-858.
[19] Chen M C, Anderson J R, Sohn M H. What can a mouse cursor tell us more? correlation of eye/mouse movements on web browsing[C]// CHI'01 Extended Abstracts on Human Factors in Computing Systems. ACM, 2001:281-282.
[20] Gwizdka J, Jose J, Mostafa J, et al. NeuroIR 2015: Neuro-physiological methods in IR research[J].ACM SIGIR Forum, 2015,49(2):83-88.
[21] Xu S, Jiang H, Lau F C M. Observing facial expressions and gaze positions for personalized webpage recommendation[C]// International Conference on Electronic Commerce: Roadmap for the Future of Electronic Business, 2010:78-87.
[22] Kn?usl H, Ludwig B. Assessing the relationship between context, user preferences, and content in search behaviour[C]//Proceedings of the 5th Ph.D. Workshop on Information and Knowledge. ACM, 2012:67-74.
[23] Smith C L, Gwizdka J, Feild H. Exploring the use of query auto completion: search behavior and query entry profiles[C]// Proceedings of the 2016 ACM on Conference on Human Information Interaction and Retrieval, 2016:101-110.
[24] Dewitt A J. Examining the order effect of website navigation menus with eye tracking[M]. Usability Professionals' Association, 2010.
[25] Bilal D, Gwizdka J. Children's eye-fixations on google search results[C]// Asist & Meeting: Creating Knowledge, Enhancing Lives Through Information & Technology. American Society for Information Science, 2016:89.
[26] P?ivi M, Aula A. Effects of feedback on eye typing with a short dwell time[C]// Symposium on Eye Tracking Research & Applications. ACM, 2004:139-146.
[27] Muralidharan A, Gyongyi Z, Chi E. Social annotations in web search[C]//Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2012:1085-1094.
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