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Do batch and user evaluations give the same results?
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Source Annual ACM Conference on Research and Development in Information Retrieval archive
Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval table of contents
Athens, Greece
Pages: 17 - 24  
Year of Publication: 2000
ISBN:1-58113-226-3
Authors
William Hersh  Division of Medical Informatics & Outcomes Research, Oregon Health Sciences University, Portland, OR
Andrew Turpin  Division of Medical Informatics & Outcomes Research, Oregon Health Sciences University, Portland, OR
Susan Price  Division of Medical Informatics & Outcomes Research, Oregon Health Sciences University, Portland, OR
Benjamin Chan  Division of Medical Informatics & Outcomes Research, Oregon Health Sciences University, Portland, OR
Dale Kramer  Division of Medical Informatics & Outcomes Research, Oregon Health Sciences University, Portland, OR
Lynetta Sacherek  Division of Medical Informatics & Outcomes Research, Oregon Health Sciences University, Portland, OR
Daniel Olson  Division of Medical Informatics & Outcomes Research, Oregon Health Sciences University, Portland, OR
Sponsors
Athens U of Econ & Business : Athens University of Economics and Business
Greek Com Soc : Greek Computer Society
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 4,   Downloads (12 Months): 60,   Citation Count: 22
Additional Information:

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ABSTRACT

Do improvements in system performance demonstrated by batch evaluations confer the same benefit for real users? We carried out experiments designed to investigate this question. After identifying a weighting scheme that gave maximum improvement over the baseline in a non-interactive evaluation, we used it with real users searching on an instance recall task. Our results showed the weighting scheme giving beneficial results in batch studies did not do so with real users. Further analysis did identify other factors predictive of instance recall, including number of documents saved by the user, document recall, and number of documents seen by the user.


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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C. Cleverdon and E. Keen, Factors determining the performance of indexin systems, Cranfield UK: Aslib Cranfield Research Project 1966.
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C. Meadow, Relevance?, Journal of the American Society for Information Science, 36: 354-355, 1985.
 
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D. Swanson, Information retrieval as a trial-anderror process, Library Quarterly, 47: 128-148, 1977.
 
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CITED BY  22

Collaborative Colleagues:
William Hersh: colleagues
Andrew Turpin: colleagues
Susan Price: colleagues
Benjamin Chan: colleagues
Dale Kramer: colleagues
Lynetta Sacherek: colleagues
Daniel Olson: colleagues