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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 3 of 3 1 On the Reliability of Test Collections for Evaluating Systems of Different Types ... Yilmaz, Emine; Craswell, Nick; Mitra, Bhaskar; Campos, Daniel. - : arXiv, 2020 Abstract: As deep learning based models are increasingly being used for information retrieval (IR), a major challenge is to ensure the availability of test collections for measuring their quality. Test collections are generated based on pooling results of various retrieval systems, but until recently this did not include deep learning systems. This raises a major challenge for reusable evaluation: Since deep learning based models use external resources (e.g. word embeddings) and advanced representations as opposed to traditional methods that are mainly based on lexical similarity, they may return different types of relevant document that were not identified in the original pooling. If so, test collections constructed using traditional methods are likely to lead to biased and unfair evaluation results for deep learning (neural) systems. This paper uses simulated pooling to test the fairness and reusability of test collections, showing that pooling based on traditional systems only can lead to biased evaluation of deep ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Information Retrieval cs.IR; Machine Learning cs.LG URL: https://dx.doi.org/10.48550/arxiv.2004.13486 https://arxiv.org/abs/2004.13486 BASE Hide details 2 Frontiers, Challenges, and Opportunities for Information Retrieval – Report from SWIRL 2012, The Second Strategic Workshop on Information Retrieval in Lorne Kelly, Diane; Clarke, Charles L.A.; Moffat, Alistair. - : KTH, Teoretisk datalogi, TCS, 2012. : ACM, 2012 BASE Show details 3 Microsoft Research at TREC 2009. Web and Relevance Feedback Tracks Craswell, Nick; Fetterly, Dennis; Najork, Marc... In: DTIC (2009) BASE Show details

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