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Visualizing implicit queries for information management and retrieval
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Source Conference on Human Factors in Computing Systems archive
Proceedings of the SIGCHI conference on Human factors in computing systems: the CHI is the limit table of contents
Pittsburgh, Pennsylvania, United States
Pages: 560 - 567  
Year of Publication: 1999
ISBN:0-201-48559-1
Authors
Mary Czerwinski  Microsoft Research, One Microsoft Way, Redmond, WA
Susan Dumais  Microsoft Research, One Microsoft Way, Redmond, WA
George Robertson  Microsoft Research, One Microsoft Way, Redmond, WA
Susan Dziadosz  Microsoft Research, One Microsoft Way, Redmond, WA
Scott Tiernan  Microsoft Research, One Microsoft Way, Redmond, WA
Maarten van Dantzich  Microsoft Research, One Microsoft Way, Redmond, WA
Sponsor
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 15,   Downloads (12 Months): 77,   Citation Count: 10
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ABSTRACT

In this paper, we describe the use of similarity metrics in a novel visual environment for storing and retrieving favorite web pages. The similarity metrics, called Implicit Queries, are used to automatically highlight stored web pages that are related to the currently selected web page. Two experiments explored how users manage their personal web information space with and without the Implicit Query highlighting and later retrieve their stored web pages. When storing and organizing web pages, users with Implicit Query highlighting generated slightly more categories. Implicit Queries also led to faster web page retrieval time, although the results were not statistically significant.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Craik, F.I.M. & Lockhart, R.S. (1972). Levels of processing: A framework for memory research. Journal of Verbal Learning and Verbal Behaviour, 1 l, 671-684.
 
3
Dumais, S.T. (1988). Textual information retrieval. In M. Helander (Ed.) Handbook of Human-Computer Interaction. Elsevier Science Publishers (North Holland)..
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Horvitz, E., Breese, J., Heckerman, D., Hovel. D. & Rommelse, K. (1998). The Lumiere project: Bayesian user modeling for inferring the goals and needs of software users. Proceedings of the Fourteenth Conference on Uncertainty in Artificial intelligence.
 
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Kehoe, C., Pitkow, J. & Rogers, J. (1998). GVU's 9th WWW User Survey, http ://www. gvu. gatech.edu/user surveys
 
8
9
 
10
11
 
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Rhodes, B. and Starner, T. A continuously running automated information retrieval system. In Proceedings of The First International Conference on The Practical Application of Intelligent Agents and Multi Agent Technology (PAAM '96), London, UK, April 1996, pp. 487-495.
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Tullis, T.S. (1997). Screen Design. In (Eds.) Helander, M., Landauer, T.K. & Prabhu, P.'s, Handbook of human-computer interaction, 2nd Edition, Elsevier Science, B.V., 503-531.
 
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CITED BY  10

Collaborative Colleagues:
Mary Czerwinski: colleagues
Susan Dumais: colleagues
George Robertson: colleagues
Susan Dziadosz: colleagues
Scott Tiernan: colleagues
Maarten van Dantzich: colleagues