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Communication Dans Un Congrès Année : 2005

Using RankBoost to Compare Retrieval systems

Résumé

This paper presents a new pooling method for constructing the assessment sets used in the evaluation of retrieval systems. Our proposal is based on RankBoost, a machine learning voting algorithm. It leads to smaller pools than classical pooling and thus reduces the manual assessment workload for building test collections. Experimental results obtained on an XML document collection demonstrate the effectiveness of the approach according to different evaluation criteria.
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Dates et versions

hal-01490516 , version 1 (15-03-2017)

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Huyen-Trang Vu, Patrick Gallinari. Using RankBoost to Compare Retrieval systems. CIKM 2005 - 14th ACM international conference on Information and knowledge management, Oct 2005, Bremen, Germany. pp.309-310, ⟨10.1145/1099554.1099641⟩. ⟨hal-01490516⟩
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