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MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification
Ye Zhang
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Stephen Roller
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Byron C. Wallace
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Paper Details:
Month: June
Year: 2016
Location: San Diego, California
Venue:
NAACL |
Citations
URL
Learning What to Share: Leaky Multi-Task Network for Text Classification
Liqiang Xiao
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Honglun Zhang
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Wenqing Chen
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Yongkun Wang
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Yaohui Jin
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A Hybrid CNN-RNN Alignment Model for Phrase-Aware Sentence Classification
Shiou Tian Hsu
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Changsung Moon
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Paul Jones
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Nagiza Samatova
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From Random to Supervised: A Novel Dropout Mechanism Integrated with Global Information
Hengru Xu
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Shen Li
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Renfen Hu
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Si Li
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Sheng Gao
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Learning Word Meta-Embeddings
Wenpeng Yin
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Hinrich Schütze
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Harnessing Deep Neural Networks with Logic Rules
Zhiting Hu
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Xuezhe Ma
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Zhengzhong Liu
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Eduard Hovy
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Eric Xing
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Assessing the Corpus Size vs. Similarity Trade-off for Word Embeddings in Clinical NLP
Kirk Roberts
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Automatic classification of doctor-patient questions for a virtual patient record query task
Leonardo Campillos Llanos
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Sophie Rosset
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Pierre Zweigenbaum
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Identifying Key Sentences for Precision Oncology Using Semi-Supervised Learning
Jurica Ševa
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Martin Wackerbauer
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Ulf Leser
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https://code.google.com/p/word2vec/
http://nlp.stanford.edu/projects/glove/
https://bitbucket.org/yoavgo/word2vecf/
Field Of Study
Linguistic Trends
Distributional Semantics
Embeddings
Task
Sentiment Analysis
Text Categorization
Language
English
Dataset
News
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