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研究生: 林弘緯
Lin, Hung-Wei
論文名稱: 辨識跨期程任務以協助探索式網頁搜尋
Facilitating Exploratory Web Search by Recognizing Cross-Session Tasks
指導教授: 鄧維光
Teng, Wei-Guang
學位類別: 碩士
Master
系所名稱: 工學院 - 工程科學系
Department of Engineering Science
論文出版年: 2015
畢業學年度: 103
語文別: 英文
論文頁數: 53
中文關鍵詞: 探索式搜尋歷程紀錄跨期程任務搜尋意圖
外文關鍵詞: exploratory search, browsing log, cross-session search tasks, search intent
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  • 在現在網路普及的世界裡,數位化的資料正以大量且快速的方式累積,其資訊量已大至無法讓使用者逐一閱覽並過濾資料以滿足其搜尋意圖,因此造成了資訊過載的問題。而網頁搜尋引擎的問世和關鍵詞搜尋的方法則有效地解決了此情形,讓使用者多能夠在短時間內獲取自身想要的資訊。然而當使用者在搜尋自身不太了解的主題時,往往還是得花費大量的時間在過濾結果以及重新進行查詢上,此一過程被稱為探索式搜尋,且據前人研究指出這類的搜尋在所有搜尋行為中佔了大多數比例;而探索式搜尋之過程往往是不連續的、且每次搜尋結果內可能會充斥著許多雜訊,這種不連續的搜尋過程又可稱作跨期程的任務 (cross-session tasks),而如何能夠自動辨識出跨期程間相關的搜尋任務,並且妥善地儲存和重複使用這些資料,將是一重要的研究課題。為此我們提出了一個系統架構與對應的資料處理流程,當使用者在進行探索式搜尋的同時,即能同步地收集其瀏覽歷程等相關資訊並加以分析,以供後續的使用者重複利用而更有效地簡化其搜尋過程;最後我們除了以實作出的原型系統請受試者實際使用以給予評估外,並將不同主題中所需花費之搜尋時間與直接使用搜尋引擎時加以比較,可驗證得知我們所提之系統普遍而言均能協助使用者較快速地完成探索式搜尋。

    With the widespread of Internet, a massive amount of information is explosively accumulated in digital form today. It is almost impossible for users to review all of the information in details for satisfying their search intent. Such a problem of data overloading is then alleviated by search engines and the mechanism of keyword search. However, information seekers may still need much time to find out the useful information when they face unfamiliar topics. Specifically, much time can be spent on reformulating query terms and digesting the knowledge from search results. Such an information seeking process is called exploratory search that constitutes a large portion of web search activities. In addition, search tasks within the exploratory search process are usually cross-sessional, discontinuous and full of noises. Therefore, how to automatically recognize such exploratory search processes and reuse them is a crucial issue. In this work, we thus propose a prototype system to collect and reuse the corresponding information so as to facilitate the search process. Specifically, our system firstly distinguishes the search intent when a user starts his/her initial web search and when he/she reads the search results. To further help a user when he/she is starting an exploratory search, possible query terms are provided for him/her to conduct more search sessions whereas similar search patterns from other users are shown as a reference. Moreover, we devise improved user interfaces so that users can easily review their personal searching activities. Finally, we have several volunteer participants joining the experimental studies to test our prototype system. The time that participants spend on different topics when using our system and Google search engine is recorded. Experimental results show that our prototype system do help users to accomplish their exploratory search in a more efficient way.

    Chapter 1 Introduction 1 1.1 Motivation and Overview 1 1.2 Contributions of This Work 3 Chapter 2 Preliminaries 4 2.1 Relevance of Web Search and Social Networks 4 2.2 User Intent in Web Search 5 2.3 Search Sessions 7 2.4 An Overview of Exploratory Search 9 2.4.1 Features of Information Seeking Process 9 2.4.2 Improving the Exploratory Search 11 Chapter 3 Supporting Users in the Exploratory Search Process 14 3.1 Predicaments in the Exploratory Search Process 14 3.2 Identifying Exploratory Search Behavior 17 3.3 Features of Our Proposed Scheme 21 Chapter 4 System Prototyping and Evaluation 25 4.1 Prototype Implementation 25 4.2 System Features 26 4.2.1 Information Reutilization 26 4.2.2 Personal and Privacy Issues 28 4.3 Evaluation Results 29 Chapter 5 Conclusions and Future Works 41 Bibliography 42 Appendix A SUMI Questionnaire (in English) 47 Appendix B SUMI Questionnaire (in Chinese) 51

    [1] E. Agichtein, R.-W. White, S.-T. Dumais, and P. N Bennet, “Search, Interrupted: Understanding and Predicting Search Task Continuation.” Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 315-324, August 2012.
    [2] J.-W. Ahn, K. Wongsuphasawat, and P. Brusilovsky, "Analyzing User Behavior Patterns in Adaptive Exploratory Search Systems with Lifeflow," October 2011
    [3] K.-M. Athukorala, "Enhancing Exploratory Information-Seeking through Interaction Modeling," User Modeling, Adaptation, and Personalization, pages 478-483, July 2014.
    [4] K.-M. Athukorala, "Supporting Exploratory Search through User Modeling," Extended Proceedings of the 14th Conference on User Modeling, Adaptation and Personalization, 50(1):1-10, May 2013.
    [5] M. Bates, “The Design of Browsing and Berrypicking Techniques for the Online Search Interface,” Online Review, 13(5):407-424, October 1989.
    [6] C. Charles and M. Affiliated, "Google, Tear Down This Wall to Exploratory Search!" Bulletin of the American Society for Information Science and Technology, 40(5):50-54, July 2014.
    [7] W.-L. Chen and W.-G. Teng, "Exploiting Browsing History for Exploratory Search," Proceedings of the 13th International Conference on Human-Computer Interaction, pages 355-364, July 2009.
    [8] Z. Cheng, B. Gao and T.-Y. Liu, “Actively Predicting Diverse Search Intent from User Browsing Behaviors,” Proceedings of the 19th international conference on World wide web, pages 221-230, April 2010
    [9] A. Figueroa, “Exploring Effective Features for Recognizing the User Intent behind Web Queries” Computers in Industry, 68:162-169, April 2015
    [10] H. Fu and S. Wu, ”Determining the User Intent of Chinese-English Mixed Language Queries Based On Search Logs” iConference 2015 Proceedings, 2015
    [11] G. Golovchinsky, A. Dunnigan, and A. Diriye, "Designing a Tool for Exploratory Information Seeking," CHI'12 Extended Abstracts on Human Factors in Computing Systems, pages 1799-1804, May 2012.
    [12] Q. Guo and E. Agichtein, “Ready to Buy or Just Browsing?: Detecting Web Searcher Goals from Interaction Data,” Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 130-137, July 2010.
    [13] S. Han, D. He, J. Jiang and Z. Yue, "Supporting Exploratory People Search: A Study of Factor Transparency and User Control," Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pages 449-458, October 2013.
    [14] B. Hecht, J. Teevan, M.-R. Morris and D. Liebling, "SearchBuddies: Bringing Search Engines into the Conversation," Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media, pages 138-145, June 2012.
    [15] M. Hemmje, A. Stein, and H.-D. Boecker, "A Multidimensional Categorization of Information Activities for Differential Design and Evaluation of Information Systems," 1996.
    [16] B.-J. Jansen, D.-L. Booth, and A. Spink, "Determining the Informational, Navigational, and Transactional Intent of Web Queries," Information Processing & Management, 40(3):1251-1266, May 2008.
    [17] T. Jiang, "Exploratory Search: A Critical Analysis of the Theoretical Foundations, System Features, and Research Trends," Springer Berlin Heidelberg, pages 79-103, October 2014.
    [18] Y. Jia and X. Niu, "Should I Stay or Should I Go: Two Features to Help People Stop An Exploratory Search Wisely," Proceedings of ACM CHI'14 Extended Abstracts on Human Factors in Computing Systems, pages 1357-1362, April 2014.
    [19] R. Jones, and K.-L. Klinkner, “Beyond the Session Timeout: Automatic Hierarchical Segmentation of Search Topics in Query Logs.” Proceedings of the 17th ACM conference on Information and Knowledge Management, pages 699-708, October 2008.
    [20] S. Joo and I. Xie, "How Do Users' Search Tactic Selections Influence Search Outputs in Exploratory Search Tasks?" Proceedings of the 13th ACM/IEEE-CS Joint Conference on Digital Libraries, pages 397-398, July 2013
    [21] A. Kotov, P.-N. Bennett and R.-W. White, S.-T. Dumais and J. Teevan, "Modeling and Analysis of Cross-session Search Tasks," Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 5-14, July 2011.
    [22] Z. Liao, Y. Song, L.-W. He and Y. Huang, “Evaluating the Effectiveness of Search Task Trails.” Proceedings of the 21st International Conference on World Wide Web, pages 489-498, April 2012.
    [23] C. Lucchese, O. Salvatore, P. Raffaele, F. Silvestri and G. Tolomei, "Identifying Task-based Sessions in Search Engine Query Logs." Proceedings of the Fourth ACM International Conference on Web Search and Data Mining, pages 277-286, February 2011.
    [24] G. Marchionini, "Exploratory Search: From Finding to Understanding," Communications of the ACM, 49(4):41-46, April 2006.
    [25] A. Oeldorf - Hirsch, B. Hecht, M. - R. Morris, J. Teevan and D. Gergle, "To Search or to Ask: The Routing of Information Needs Between Traditional Search Engines and Social Networks," Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work & Social Computing, pages 16-27, February 2014.
    [26] Y.-C. Peng, C.-C. Chang, W.-G. Teng and C.-M. Wu, ”Exploiting Collective Intelligence for Asynchronous Collaborative Search,” Proceedings of the 2nd IEEE Global Conference on Consumer Electronics, pages 129-130, October 2013.
    [27] M.-A. Potey, D.-A Patel and P.-K Sinha, “A survey of query log processing techniques and evaluation of web query intent identification,” Advance Computing Conference (IACC), pages 1330-1335, February 2013
    [28] X. Ren, Y. Wang, X. Yu, J. Yan, Z. Chen and J. Han, “Heterogeneous Graph-based Intent Learning with Queries, Web Pages and Wikipedia Concepts,” Proceedings of the 7th ACM International Conference on Web Search and Data Mining, pages 23-32, February 2014
    [29] T. Ruotsalo, K. Athukorala, D. Głowacka, K. Konyushkova, A. Oulasvirta, S. Kaipiainen, S. Kaski and G. Jacucci, “Supporting Exploratory Search Tasks with Interactive User Modeling” Proceedings of the American Society for Information Science and Technology, 50(1):1-10, May 2014.
    [30] Y. Shen, Y. Li, Y. Xu, R. Iannella, A. Algarni and X. Tao, “An Ontology-based Mining Approach for User Search Intent Discovery,” Proceedings of the Sixteenth Australasian Document Computing Symposium, pages 39-46, December 2011.
    [31] G. Singer, U. Norbisrath, E. Vainikko, H. Kikkas, D. Lewandowski, "Search-logger Analyzing Exploratory Search Tasks," Proceedings of the 2011 ACM Symposium on Applied Computing, pages 751-756, May 2011.
    [32] B. Smyth, and E. Balfe,” Anonymous Personalization in Collaborative Web Search.” Information Retrieval, 9(2): 165-190, March 2006.
    [33] Y. Song, H. Ma, H. Wang, K. Wang, "Exploring and Exploiting User Search Behavior on Mobile and Tablet Devices to Improve Search Relevance," Proceedings of the 22nd International Conference on World Wide Web, pages 1201-1212, May 2013.
    [34] J. Teevan, D. Ramage, and M. - R. Morris, "# TwitterSearch: A Comparison of Microblog Search and Web Search," Proceedings of the Fourth ACM International Conference on Web Search and Data Mining, pages 35-44, February 2011.
    [35] W.-G. Teng, W.-H. Wen, and Y.-C. Liu, "From Experience to Expertise: Digesting Cumulative Information for Informational Web Search," Journal of Information Science and Engineering, 28(1):161-176, January 2012.
    [36] S. Verberne, M. Heijden, M. Hinne, M. Sappelli, S. Koldijk, E. Hoenkamp and W. Kraaij, “Reliability and Validity of Query Intent Assessments,” Journal of the American Society for Information Science and Technology, 64(11): 2224-2237, November 2013.
    [37] Z. Yue, S. Han, D. He, and J. Jiang, "Influences on Query Reformulation in Collaborative Web Search." IEEE Computer Society, 47(3):46-53, March 2014.

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