12 citations · 19 across the 2 of their papers we have counts for
2 papers
cs.IR2017★ 7 cited
An Exploration of Approaches to Integrating Neural Reranking Models in Multi-Stage Ranking Architectures
Zhucheng Tu, Matt Crane, Royal Sequiera +2
We explore different approaches to integrating a simple convolutional neural network (CNN) with the Lucene search engine in a multi-stage ranking architecture. Our models are train…
cs.IR2017★ 12 cited
Efficient and Effective Tail Latency Minimization in Multi-Stage Retrieval Systems
Joel Mackenzie, J. Shane Culpepper, Roi Blanco +3
Scalable web search systems typically employ multi-stage retrieval architectures, where an initial stage generates a set of candidate documents that are then pruned and re-ranked.…