A Comparative Study of Context-Based Information Refinding
Keywords:
Information refinding, Context cue, refinding queriesAbstract
We present a comparative study of query analysis for efficient context -based information refinding system. Refinding what we have done before is a common behavior of human in real life. According to the human natural recall characteristics, users allow to refinding web pages which have seen before. Psychological studies show that context under which information was accessed can helps as a powerful cue for information recall. Here context including time, place and concurrent activity could serves as a useful information recall clues. We build a recall based query model, linking to the previous accessed information contents. We explore the use of context cluster and association to efficiently process the context based refinding queries. In context memory dynamically evolve in life cycles; there are memory’s decay and reinforcement phenomena. Thus take contextual information refinding of various paper and make comparison of how to contextual cues to refind the Web Pages effectively.
References
GoogleWeb History, http://www.google.com/history, 2013.
Tangjian Deng, Liang Zhao, Hao Wang, Qingwei Liu, and Ling Feng, Senior Member, IEEE “ReFinder: A Context-Based Information Refinding System”
S. Won, J. Jin, and J. Hong, “Conte xtual Web History: Using Visual and Contextual Cues to Improve Web Browser History,” Proc.SIGCHI Conf. Human Factors in Computing Systems (CHI), 2009.
B. MacKay, M. Kellar, and C. Watters, “An Evaluation of Landmarks for Re-Finding Information on the Web,” Proc. Extended Abstracts on Human Factors in Computing Systems (CHI ’05 EA), 2005.
J. Hailpern, N. Jitkoff, A. Warr, R. Karahalios, K. Sesek, andN. Shkrob, “YouPivot: Improving Recall with Contextual Search,” Proc. SIGCHI Conf. Human Factors in Computing Systems (CHI), 2011.
E. Adar, J. Teevan, and S.T. Dumais, “Large Scale Analysis of Web Revisitation Patterns,” Proc. SIGCHI Conf. Human Factors in Computing Systems (CHI), 2008.
R. Capra, M. Pinney, and M.A. Perez-Quinones, “Refinding Is Not Finding Again,” technical report, Aug. 2005.
Y. Chen and G. Jones, “Integrating Memory Context into Personal Information Re-Finding,” Proc. Second Symp. Future Directions in Information Access, 2008
J. Teevan, “The Re:Search Engine: Simultaneous Support for Finding and Re-Finding,” Proc. 20th Ann. ACM Symp. User Interface Software and Technology (UIST), 2007.
S.K. Tyler and J. Teevan, “Large Scale Query Log Analysis of Re-Finding,” Proc. Third ACM Int’l Conf. Web Search and Data Mining(WSDM), 2010.
A.P.Nivethitha“efficiently context-based information re-finding and page ranking”International conference on electrical, communication and computing,2014.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2014 COMPUSOFT: An International Journal of Advanced Computer Technology
This work is licensed under a Creative Commons Attribution 4.0 International License.
©2023. COMPUSOFT: AN INTERNATIONAL OF ADVANCED COMPUTER TECHNOLOGY by COMPUSOFT PUBLICATION is licensed under a Creative Commons Attribution 4.0 International License. Based on a work at COMPUSOFT: AN INTERNATIONAL OF ADVANCED COMPUTER TECHNOLOGY. Permissions beyond the scope of this license may be available at Creative Commons Attribution 4.0 International Public License.
