An Empirical Study on Web Search Behavior through the Investigation of a User-Clustered Query Session

Web search behavior is being diversified. And the diversification of web search behavior makes query both sporadic and non-sequential. In this case, it is difficult to understand why and how users search any information. Context of web search makes it possible to classify sporadic and nonsequential queries according to each interest. However, only the user him/herself can identify the context of web search behavior exactly. Hence, it is necessary to conduct a client-side research in which users are deeply engaged. The purpose of this research is to develop and apply the methodology that systematically examines the web search behavior and its context. To achieve this, (1) client-side log data is collected, then participants (2) clustered the queries based on context and (3) filled in a questionnaire as to each clustered queries. Also, interviews were conducted in each person. The finding of this study is that the features of UCQS are different from previous studies. Furthermore, we identified the flow of users' web search behavior.

[1]  Tefko Saracevic,et al.  The Stratified Model of Information Retrieval Interaction: Extension and Applications , 1997 .

[2]  Amanda Spink,et al.  Defining a session on Web search engines: Research Articles , 2007 .

[3]  K. Fisher,et al.  Theories of information behavior , 2005 .

[4]  James E. Pitkow,et al.  Characterizing Browsing Strategies in the World-Wide Web , 1995, Comput. Networks ISDN Syst..

[5]  Amanda Spink,et al.  Defining a session on Web search engines , 2007, J. Assoc. Inf. Sci. Technol..

[6]  Monika Henzinger,et al.  Analysis of a very large web search engine query log , 1999, SIGF.

[7]  Aristides Gionis,et al.  The query-flow graph: model and applications , 2008, CIKM '08.

[8]  Amanda Spink,et al.  Multitasking during Web search sessions , 2006, Inf. Process. Manag..

[9]  Bernard J. Jansen,et al.  A review of web searching studies and a framework for future research , 2001 .

[10]  Amanda Spink,et al.  How are we searching the World Wide Web? A comparison of nine search engine transaction logs , 2006, Inf. Process. Manag..

[11]  Amanda Spink,et al.  Model for organizational knowledge creation and strategic use of information: Research Articles , 2005 .

[12]  Ravin Balakrishnan,et al.  A study of tabbed browsing among mozilla firefox users , 2010, CHI.

[13]  Colleen Cool The Concept of Situation in Information Science. , 2001 .

[14]  Amanda Spink,et al.  Information Searching Tactics of Web Searchers , 2007, ASIST.

[15]  Pertti Vakkari,et al.  Task-based information searching , 2005, Annu. Rev. Inf. Sci. Technol..

[16]  Diane Kelly,et al.  The effects of topic familiarity on information search behavior , 2002, JCDL '02.

[17]  Nicholas J. Belkin,et al.  Modeling Multiple Information Seeking Episodes. , 2000 .

[18]  Carolyn Watters,et al.  A field study characterizing Web-based information-seeking tasks , 2007 .

[19]  Amanda Spink,et al.  Real life information retrieval: a study of user queries on the Web , 1998, SIGF.

[20]  Amanda Spink,et al.  Real life, real users, and real needs: a study and analysis of user queries on the web , 2000, Inf. Process. Manag..

[21]  Birger Larsen,et al.  Proceedings of the ACM SIGIR 2005 Workshop on Information Retrieval in Context (IRiX) , 2005 .

[22]  Rosie Jones,et al.  Beyond the session timeout: automatic hierarchical segmentation of search topics in query logs , 2008, CIKM '08.

[23]  Ian Ruthven,et al.  Information Retrieval in Context , 2011, Advanced Topics in Information Retrieval.

[24]  Christoph Hölscher How Internet Experts Search For Information On The Web , 1998, WebNet.

[25]  Amanda Spink,et al.  A temporal comparison of AltaVista Web searching , 2005, J. Assoc. Inf. Sci. Technol..

[26]  Peter G. Anick Using terminological feedback for web search refinement: a log-based study , 2003, SIGIR.

[27]  Brian Detlor,et al.  Information Seeking on the Web: An Integrated Model of Browsing and Searching , 2000, First Monday.

[28]  Daqing He,et al.  Detecting session boundaries from Web user logs , 2000 .