Publication | Closed Access
A simple and efficient sampling method for estimating AP and NDCG
232
Citations
14
References
2008
Year
Unknown Venue
EngineeringComplete JudgmentsMeasurementIntelligent Information RetrievalSpectrum EstimationText MiningNatural Language ProcessingInformation RetrievalData ScienceData MiningCalibrationComputational LinguisticsRelevance FeedbackBiostatisticsQuery ExpansionEstimation TheoryStatisticsConfidence IntervalsKnowledge DiscoverySampling TheorySampling (Statistics)Computer ScienceSignal ProcessingExtensive EffortStatistical InferenceTest CollectionInteractive Information Retrieval
We consider the problem of large scale retrieval evaluation. Recently two methods based on random sampling were proposed as a solution to the extensive effort required to judge tens of thousands of documents. While the first method proposed by Aslam et al. [1] is quite accurate and efficient, it is overly complex, making it difficult to be used by the community, and while the second method proposed by Yilmaz et al., infAP [14], is relatively simple, it is less efficient than the former since it employs uniform random sampling from the set of complete judgments. Further, none of these methods provide confidence intervals on the estimated values.
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