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New Technology of Library and Information Service  2014, Vol. 30 Issue (2): 32-40    DOI: 10.11925/infotech.1003-3513.2014.02.05
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A Review on Web Navigation Model:Information Foraging Theory Perspective
Ke Qing, Wang Xiufeng
Information Management School, Nanjing University, Nanjing 210093, China
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Abstract  

[Objective] This paper aims to analyze the Web navigation models based on information foraging theory. [Method] The paper compares the similarities of the foraging behavior of animals and navigation behavior of users, investigates the theory foundations of Web navigation models based on information foraging theory and analyzes the operating mechanism of SNIF-ACT series models. [Results] The Web navigation models based on information foraging theory describe users' cognitive characteristics under limited rational hypothesis and suboptimal decision situations. [Conclusion] The paper provides some suggestions so as to improve the application of these models in explaining and predicting users' Web navigation behavior.

Key wordsInformation foraging      Web navigation      Model      Review     
Received: 19 July 2013      Published: 06 March 2014
PACS:  G203  

Cite this article:

Ke Qing, Wang Xiufeng. A Review on Web Navigation Model:Information Foraging Theory Perspective. New Technology of Library and Information Service, 2014, 30(2): 32-40.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2014.02.05     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2014/V30/I2/32

Miller C S, Remington R W. Modeling Information Navigation: Implications for Information Architecture[J]. Human-Computer Interaction, 2004, 19(3): 225-271.
Pirolli P, Card S K. Information Foraging[J]. Psychological Review, 1999, 106 (4): 643-675.
Jul S, Furnas G W. Navigation in Electronic Worlds: A CHI 97 Workshop[EB/OL].[2011-09-01]. http://homepages.cwi.nl/~steven/sigchi/bulletin/1997.4/jul. html.
Pirolli P, Fu W. SNIF-ACT: A Model of Information Foraging on the World Wide Web[C]. In: Proceedings of the 9th International Conference on User Modeling (UM'03). Heidelberg: Springer-Verlag, 2003: 45-54.
Fu W, Pirolli P. SNIF-ACT: A Cognitive Model of User Navigation on the World Wide Web[J]. Human-Computer Interaction, 2007, 22 (4): 355-412.
郝伯特.A.西蒙. 管理行为[M]. 詹正茂译. 原书第4版. 北京: 机械工业出版社, 2007: 15. (Simon H A. Administrative Behavior: A Study of Decision-Making Processes in Administrative Organizations[M]. Translated by Zhan Zhengmao. The 4th Edition. Beijing: China Machine Press, 2007: 15.)
Anderson J R. The Adaptive Character of Thought[M]. Psychology Press, 1990.
Oaksford M, Chater N. Rational Explanation of the Selection Task[J]. Psychological Review, 1996, 103 (2): 381-391.
Fu W, Gray W D. Suboptimal Tradeoffs in Information Seeking[J]. Cognitive Psychology, 2006, 52 (3): 195-242.
Annan K. If Information and Knowledge are Central to Democracy, They are Conditions for Development[EB/OL].[2013-11-14]. http://www.un.org/News/Press/docs/1997/1997 0623. sgsm6268.html.
Pirolli P. Information Foraging Theory: Adaptive Interaction with Information[M]. New York: Oxford University Press, 2007: 89-109.
Anderson J R, Lebiere C J. The Atomic Components of Thought[M]. Hillsdale, NJ: Lawrence Erlbaum Associates, 1998.
Rumelhart D E, McClelland J L. Interactive Processing Through Spreading Activation[A].//Perfetti C A, Lesgold A M. Interactive Processes in Reading[M]. Hillsdale, NJ: Lawrence Erlbaum Associates, 1981.
Joachims T, Granka L, Pang B, et al. Accurately Interpreting Clickthrough Data as Implicit Feedback[C]. In: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'05). New York: ACM, 2005: 154-161.
Chi E H, Pirolli P, Chen K, et al. Using Information Scent to Model User Information Needs and Actions on the Web[C]. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI'01), Seattle, WA, USA. New York: ACM, 2001: 490-497.
van Oostendorp H, Karanam S, Indurkhya B. CoLiDeS+Pic: A Cognitive Model of Web-navigation Based on Semantic Information from Pictures[J]. Behaviour & Information Technology, 2012, 31(1): 17-30.
杨阳, 张新民. 信息觅食理论的研究进展[J]. 现代图书情报技术, 2009(1): 73-79. (Yang Yang, Zhang Xinmin. Advance in Information Foraging Theory[J]. New Technology of Library and Information Service, 2009(1): 73-79.
Kitajima M, Toyota M. Simulating Navigation Behaviour Based on the Architecture Model Human Processor with Real-Time(MHP/RT)[J]. Behaviour & Information Techn-ology, 2012, 31(1): 41-58.
Nielsen J. Designing Web Usability[M]. Indianapolis: New Riders, 2000.
Chi E H, Rosien A, Suppattanasiri G, et al. The Bloodhound Project: Automating Discovery of Web Usability Issues Using the InfoScent Simulator[C]. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI'03). New York: ACM, 2003: 505-512.
Katsanos C, Tselios N, Avouris N. Evaluating Website Navigability: Validation of a Tool-based Approach Through Two Eye-tracking User Studies[J]. The New Review of Hypermedia and Multimedia, 2010, 16 (1-2): 195-214.
Blackmon M H, Kitajima M, Polson P G. Tool for Accurately Predicting Website Navigation Problems, Non-problems, Problem Severity, and Effectiveness of Repairs[C]. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI'05), Portland, Oregon, USA. New York: ACM, 2005: 31-40.
Budiu R, Pirolli P L. Modeling Navigation in Degree of Interest Trees[C]. In: Proceedings of the 29th Annual Conference of the Cognitive Science Society, Nashville, TN, USA. 2007: 845-850.
Blackmon M H. Information Scent Determines Attention Allocation and Link Selection Among Multiple Information Patches on a Webpage[J]. Behaviour & Information Techno-logy, 2012, 31(1): 3-15.
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