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NPRF: A Neural Pseudo Relevance Feedback Framework for Ad-hoc
  Information Retrieval

NPRF: A Neural Pseudo Relevance Feedback Framework for Ad-hoc Information Retrieval

30 October 2018
Canjia Li
Yingfei Sun
Xianpei Han
Le Wang
Kai Hui
Andrew Yates
Le Sun
Jungang Xu
ArXiv (abs)PDFHTML

Papers citing "NPRF: A Neural Pseudo Relevance Feedback Framework for Ad-hoc Information Retrieval"

5 / 5 papers shown
Title
End-to-End Neural Ad-hoc Ranking with Kernel Pooling
End-to-End Neural Ad-hoc Ranking with Kernel Pooling
Chenyan Xiong
Zhuyun Dai
Jamie Callan
Zhiyuan Liu
Russell Power
68
563
0
20 Jun 2017
PACRR: A Position-Aware Neural IR Model for Relevance Matching
PACRR: A Position-Aware Neural IR Model for Relevance Matching
Kai Hui
Andrew Yates
K. Berberich
Gerard de Melo
46
155
0
12 Apr 2017
Query Expansion with Locally-Trained Word Embeddings
Query Expansion with Locally-Trained Word Embeddings
Fernando Diaz
Bhaskar Mitra
Nick Craswell
NAI
44
270
0
25 May 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.9K
150,115
0
22 Dec 2014
Distributed Representations of Words and Phrases and their
  Compositionality
Distributed Representations of Words and Phrases and their Compositionality
Tomas Mikolov
Ilya Sutskever
Kai Chen
G. Corrado
J. Dean
NAIOCL
397
33,550
0
16 Oct 2013
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