855 citations · 2.8k across the 100 of their papers we have counts for
8 papers · 1 filter
A Deep Relevance Matching Model for Ad-hoc Retrieval
Jiafeng Guo, Yixing Fan, Qingyao Ai +1
In recent years, deep neural networks have led to exciting breakthroughs in speech recognition, computer vision, and natural language processing (NLP) tasks. However, there have be…
Locally Smoothed Neural Networks
Liang Pang, Yanyan Lan, Jun Xu +2
Convolutional Neural Networks (CNN) and the locally connected layer are limited in capturing the importance and relations of different local receptive fields, which are often cruci…
Learning Visual Features from Snapshots for Web Search
Yixing Fan, Jiafeng Guo, Yanyan Lan +3
When applying learning to rank algorithms to Web search, a large number of features are usually designed to capture the relevance signals. Most of these features are computed based…
DeepRank: A New Deep Architecture for Relevance Ranking in Information Retrieval
Liang Pang, Yanyan Lan, Jiafeng Guo +3
This paper concerns a deep learning approach to relevance ranking in information retrieval (IR). Existing deep IR models such as DSSM and CDSSM directly apply neural networks to ge…
A Deep Investigation of Deep IR Models
Liang Pang, Yanyan Lan, Jiafeng Guo +2
The effective of information retrieval (IR) systems have become more important than ever. Deep IR models have gained increasing attention for its ability to automatically learning…
MatchZoo: A Toolkit for Deep Text Matching
Yixing Fan, Liang Pang, JianPeng Hou +3
In recent years, deep neural models have been widely adopted for text matching tasks, such as question answering and information retrieval, showing improved performance as compared…