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More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction
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More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction

Xu Han
Tianyu Gao
Yankai Lin
Hao Peng
Yaoliang Yang
Chaojun Xiao
Zhiyuan Liu
Peng Li
Maosong Sun
Jie Zhou
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Papers citing "More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction"

4 / 54 papers shown
Title
Question Answering with Subgraph Embeddings
Question Answering with Subgraph Embeddings
Antoine Bordes
S. Chopra
Jason Weston
RALMBDLGNN
88
715
0
14 Jun 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
399
33,560
0
16 Oct 2013
Connecting Language and Knowledge Bases with Embedding Models for Relation Extraction
Connecting Language and Knowledge Bases with Embedding Models for Relation Extraction
Jason Weston
Antoine Bordes
Oksana Yakhnenko
Nicolas Usunier
96
245
0
30 Jul 2013
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomas Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
680
31,538
0
16 Jan 2013