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Intelligent Topic Selection for Low-Cost Information Retrieval Evaluation: A New Perspective on Deep vs. Shallow Judging
[article]
2017
arXiv
pre-print
While test collections provide the cornerstone for Cranfield-based evaluation of information retrieval (IR) systems, it has become practically infeasible to rely on traditional pooling techniques to construct test collections at the scale of today's massive document collections. In this paper, we propose a new intelligent topic selection method which reduces the number of search topics needed for reliable IR evaluation. To rigorously assess our method, we integrate previously disparate lines of
arXiv:1701.07810v4
fatcat:2jtkw26ngfdxnlfzutcw5kpopa