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- W4248570251 abstract "Ranking information retrieval (IR) systems with respect to their effectiveness is a crucial operation during IR evaluation, as well as during data fusion. This article offers a novel method of approaching the system-ranking problem, based on the widely studied idea of polyrepresentation. The principle of polyrepresentation suggests that a single information need can be represented by many query articulations–what we call query aspects. By skimming the top k (where k is small) documents retrieved by a single system for multiple query aspects, we collect a set of documents that are likely to be relevant to a given test topic. Labeling these skimmed documents as putatively relevant lets us build pseudorelevance judgments without undue human intervention. We report experiments where using these pseudorelevance judgments delivers a rank ordering of IR systems that correlates highly with rankings based on human relevance judgments." @default.
- W4248570251 created "2022-05-12" @default.
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- W4248570251 date "2010-01-01" @default.
- W4248570251 modified "2023-09-29" @default.
- W4248570251 title "Query polyrepresentation for ranking retrieval systems without relevance judgments" @default.
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- W4248570251 doi "https://doi.org/10.1002/asi.21310" @default.
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