16 citations · 28 across the 3 of their papers we have counts for
3 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★ 16 cited
Exploring the Effectiveness of Convolutional Neural Networks for Answer Selection in End-to-End Question Answering
Royal Sequiera, Gaurav Baruah, Zhucheng Tu +4
Most work on natural language question answering today focuses on answer selection: given a candidate list of sentences, determine which contains the answer. Although important, an…
cs.IR2017★ 5 cited
Integrating Lexical and Temporal Signals in Neural Ranking Models for Searching Social Media Streams
Jinfeng Rao, Hua He, Haotian Zhang +4
Time is an important relevance signal when searching streams of social media posts. The distribution of document timestamps from the results of an initial query can be leveraged to…