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Evaluating high accuracy retrieval techniques
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Source Annual ACM Conference on Research and Development in Information Retrieval archive
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval table of contents
Sheffield, United Kingdom
SESSION: Opening session table of contents
Pages: 2 - 9  
Year of Publication: 2004
ISBN:1-58113-881-4
Authors
Chirag Shah  University of Massachusetts, Amherst, MA
W. Bruce Croft  University of Massachusetts, Amherst, MA
Sponsors
ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 11,   Downloads (12 Months): 83,   Citation Count: 9
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ABSTRACT

Although information retrieval research has always been concerned with improving the effectiveness of search, in some applications, such as information analysis, a more specific requirement exists for high accuracy retrieval. This means that achieving high precision in the top document ranks is paramount. In this paper we present work aimed at achieving high accuracy in ad-hoc document retrieval by incorporating approaches from question answering(QA). We focus on getting the first relevant result as high as possible in the ranked list and argue that traditional precision and recall are not appropriate measures for evaluatin this task. We instead use the mean reciprocal rank(MRR) of the first relevant result. We evaluate three different methods for modifying queries to achieve high accuracy. The experiments done on TREC data provide support for the approach of using MRR and incorporating QA techniques for getting high accuracy in ad-hoc retrieval task.


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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CITED BY  9

Collaborative Colleagues:
Chirag Shah: colleagues
W. Bruce Croft: colleagues