2018
ACL
ACL 2018
Textual Deconvolution Saliency (TDS) : a deep tool box for linguistic analysis
Abstract
AbstractIn this paper, we propose a new strategy, called Text Deconvolution Saliency (TDS), to visualize linguistic information detected by a CNN for text classification. We extend Deconvolution Networks to text in order to present a new perspective on text analysis to the linguistic community. We empirically demonstrated the efficiency of our Text Deconvolution Saliency on corpora from three different languages: English, French, and Latin. For every tested dataset, our Text Deconvolution Saliency automatically encodes complex linguistic patterns based on co-occurrences and possibly on grammatical and syntax analysis.
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Interdisciplinary Bridge
— Artificial Intelligence and Natural Language Processing
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Trend Setter
— Syntax
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Keyword Pioneer
— deconvolution network
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Hot Topic Early Bird
— text classification
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio
Authors
Topics
Artificial Intelligence > Core AI > Interpretability
Deep Learning > Architectures > Neural Networks
Natural Language Processing > Understanding > Syntax
Natural Language Processing > Applications > Text Classification
Machine Learning > Core Methods > Feature Learning
Deep Learning > Architectures > Convolutional Neural Networks