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Syntax-Aware Multi-Sense Word Embeddings for Deep Compositional Models of Meaning
Jianpeng Cheng
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Dimitri Kartsaklis
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Paper Details:
Month: September
Year: 2015
Location: Lisbon, Portugal
Venue:
EMNLP |
SIG: SIGDAT
Citations
URL
Exploiting Word Internal Structures for Generic Chinese Sentence Representation
Shaonan Wang
|
Jiajun Zhang
|
Chengqing Zong
|
Mapping Text to Knowledge Graph Entities using Multi-Sense LSTMs
Dimitri Kartsaklis
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Mohammad Taher Pilehvar
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Nigel Collier
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Syntax Encoding with Application in Authorship Attribution
Richong Zhang
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Zhiyuan Hu
|
Hongyu Guo
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Yongyi Mao
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A Mixture Model for Learning Multi-Sense Word Embeddings
Dai Quoc Nguyen
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Dat Quoc Nguyen
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Ashutosh Modi
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Stefan Thater
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Manfred Pinkal
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Affordances in Grounded Language Learning
Stephen McGregor
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KyungTae Lim
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http://www.aclweb.org/acl-
https://github.com/cheng6076
Field Of Study
Linguistic Trends
Embeddings
Syntax
Task
Machine Translation
Paraphrasing
Approach
Deep Learning
Unsupervised Learning
Language
English
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