Effectiveness/efficiency tradeoffs for candidate generation in multi-stage retrieval architectures

Abstract

This paper examines a multi-stage retrieval architecture consisting of a candidate generation stage, a feature extraction stage, and a reranking stage using machine-learned models. Given a fixed set of features and a learning-to-rank model, we explore effectiveness/efficiency tradeoffs with three candidate generation approaches: postings intersection with… (More)
DOI: 10.1145/2484028.2484132

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