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CLASSIFICATION OF BAOULE SENTENCES ACCORDING TO FREQUENCY AND SEGMENTATION OF TERMS VIA CONVOLUTIONAL NEURAL NETWORKS

Authors: Konan, Hyacinthe Kouassi; Kouassi, Francis Adles; Diety, Guy L.;

CLASSIFICATION OF BAOULE SENTENCES ACCORDING TO FREQUENCY AND SEGMENTATION OF TERMS VIA CONVOLUTIONAL NEURAL NETWORKS

Abstract

In the Baoule language, several sentences express the same fact. Classification of sentences is a task of Natural Language Processing (NLP). Deep learning has turned out to be a kind of method that has a significant effect in this area. In this paper, we propose a convolutional neural network (CNN) based system for sentence classification. We introduce into this system a word representation model to capture semantic characteristics by encoding the frequency of terms and segmenting the sentence into clauses. The experimental results show that our system produces satisfactory results.

Keywords

Classification of Sentences CNN Frequency of Terms Segmentation

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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