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Interface and data architecture for query preview in networked information systems
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Source ACM Transactions on Information Systems (TOIS) archive
Volume 17 ,  Issue 3  (July 1999) table of contents
Pages: 320 - 341  
Year of Publication: 1999
ISSN:1046-8188
Authors
Catherine Plaisant  Human-Computer Interaction Laboratory, University of Maryland Institute for Advanced Computer Studies
Ben Shneiderman  Human-Computer Interaction Laboratory, University of Maryland Institute for Advanced Computer Studies
Khoa Doan  Human-Computer Interaction Laboratory, University of Maryland Institute for Advanced Computer Studies
Tom Bruns  Human-Computer Interaction Laboratory, University of Maryland Institute for Advanced Computer Studies
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 9,   Downloads (12 Months): 109,   Citation Count: 18
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ABSTRACT

There are numerous problems associated with formulating queries on networked information systems. These include increased data volume and complexity, accompanied by slow network access. This article proposes a new approach to a network query user interfaces that consists of two phases: query preview and query refinement. This new approach is based on the concepts of dynamic queries and query previews, which guides users in rapidly and dynamically eliminating undesired records, reducing the data volume to a manageable size, and refining queries locally before submission over a network. Examples of two applications are given: a Restaurant Finder and a prototype for NASA's Earth Observing Systems Data Information Systems (EOSDIS). Data architecture is discussed, and user feedback is presented.


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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TANIN, E., LOTEM, A., HADDADIN, I., SHNEIDERMAN, B., SLAUGHTER, L., AND PLAISANT, C. 1997. Evaluation of query previews: User preference and performance. Tech. Rep. CS-TR-3879. Department of Computer Science, University of Maryland, College Park, MD.
 
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CITED BY  18

Collaborative Colleagues:
Catherine Plaisant: colleagues
Ben Shneiderman: colleagues
Khoa Doan: colleagues
Tom Bruns: colleagues