Ranking the NTCIR ACLIA IR4QA Systems without Relevance Assessments
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概要
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We consider the problem of ranking information retrieval systems without relevance assessments in the context of collaborative evaluation forums such as NTCIR and TREC. Our short-term goal is to provide the NTCIR participants with a “system ranking forecast” prior to conducting manual relevance assessments, thereby reducing researchers “idle time” and accelarating research. The long term goal is to semi-automate repeated evaluation of search engines. Our experiments using the NTCIR-7 ACLIA IR4QA test collections show that pseudo-system-rankings based on a simple method are highly correlated with the “true” rankings. Encouraged by this positive finding, we plan to release system ranking forecasts to participants of the next round of IR4QA at NTCIR-8.
著者
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Lin Chuan-Jie
National Taiwan Ocean University
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Shima Hideki
Carnegie Mellon University
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SAKAI TETSUYA
Microsoft Research Asia
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SONG RUIHUA
Microsoft Research Asia
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MITAMURA TERUKO
Carnegie Mellon University
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Kando Noriko
National Center For Science Information Systems
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Sugimoto Miho
National Institute of Informatics
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