| Bias and the limits of pooling |
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Annual ACM Conference on Research and Development in Information Retrieval
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Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
table of contents
Seattle, Washington, USA
POSTER SESSION: Posters
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Pages: 619 - 620
Year of Publication: 2006
ISBN:1-59593-369-7
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Downloads (6 Weeks): 9, Downloads (12 Months): 60, Citation Count: 9
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ABSTRACT
Modern retrieval test collections are built through a process called pooling in which only a sample of the entire document set is judged for each topic. The idea behind pooling is to find enough relevant documents such that when unjudged documents are assumed to be nonrelevant the resulting judgment set is sufficiently complete and unbiased. As document sets grow larger, a constant-size pool represents an increasingly small percentage of the document set, and at some point the assumption of approximately complete judgments must become invalid.This paper demonstrates that the AQUAINT 2005 test collection exhibits bias caused by pools that were too shallow for the document set size despite having many diverse runs contribute to the pools. The existing judgment set favors relevant documents that contain topic title words even though relevant documents containing few topic title words are known to exist in the document set. The paper concludes with suggested modifications to traditional pooling and evaluation methodology that may allow very large reusable test collections to be built.
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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Javed A. Aslam, Virgiliu Pavlu, and Emine Yilmaz.A sampling technique for efficiently estimating measures of query retrieval performance using incomplete judgments. In Proceedings of the 22nd ICML Workshop on Learning with Partially Classified Training Data pages 57--66, August 2005.
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CITED BY 9
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Ben Carterette , Virgil Pavlu , Evangelos Kanoulas , Javed A. Aslam , James Allan, Evaluation over thousands of queries, Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, July 20-24, 2008, Singapore, Singapore
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