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A Vietnamese adjective emotion dictionary based on exploitation of Vietnamese language characteristics

A Vietnamese adjective emotion dictionary based on exploitation of Vietnamese language... Emotion classification is used in many commercial applications and research applications. The semantic classification models (or sentiment classification methods) are based on the vocabulary of the emotion dictionary being studied and being used very much to this day. In this study, a Vietnamese sentiment dictionary includes Vietnamese terms (Vietnamese nouns, Vietnamese verbs, Vietnamese adjectives, etc.) which the valences (and polarities) are calculated by using Ochiai measure through Google search engine and many Vietnamese adjective phrases which the valences (and polarities) are identified based on Vietnamese language characteristics. The Vietnamese adjectives often bear emotion which values (or semantic scores) are not fixed and are changed when they appear in different contexts of these phrases. Therefore, if the Vietnamese adjectives bring sentiment and their semantic values (or their sentiment scores) are not changed in any context, then the results of the emotion classification are not high accuracy. We propose many rules based on Vietnamese language characteristics to determine the emotional values of the Vietnamese adjective phrases bearing sentiment in specific contexts. Our Vietnamese sentiment adjective dictionary is widely used in applications and researches of the Vietnamese semantic classification. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Artificial Intelligence Review Springer Journals

A Vietnamese adjective emotion dictionary based on exploitation of Vietnamese language characteristics

A Vietnamese adjective emotion dictionary based on exploitation of Vietnamese language characteristics

Artif Intell Rev (2018) 50:93–159 https://doi.org/10.1007/s10462-017-9538-6 A Vietnamese adjective emotion dictionary based on exploitation of Vietnamese language characteristics 1 2 Vo Ngoc Phu · Vo Thi Ngoc Chau · 3 4 Vo Thi Ngoc Tran Nguyen Duy Dat Published online: 27 January 2017 © Springer Science+Business Media Dordrecht 2017 Abstract Emotion classification is used in many commercial applications and research applications. The semantic classification models (or sentiment classification methods) are based on the vocabulary of the emotion dictionary being studied and being used very much to this day. In this study, a Vietnamese sentiment dictionary includes Vietnamese terms (Vietnamese nouns, Vietnamese verbs, Vietnamese adjectives, etc.) which the valences (and polarities) are calculated by using Ochiai measure through Google search engine and many Vietnamese adjective phrases which the valences (and polarities) are identified based on Vietnamese language characteristics. The Vietnamese adjectives often bear emotion which values (or semantic scores) are not fixed and are changed when they appear in different contexts of these phrases. Therefore, if the Vietnamese adjectives bring sentiment and their semantic values (or their sentiment scores) are not changed in any context, then the results of the emotion classification are not high accuracy. We propose many rules based on Vietnamese language characteristics to determine the emotional values of the Vietnamese adjective phrases bearing sentiment in specific contexts. Our Vietnamese sentiment adjective dictionary is widely used in applications and researches of the Viet- namese semantic classification. & Vo Ngoc Phu vongocphu03hca@gmail.com; vongocphu@tdt.edu.vn; vongocphu@dtu.edu.vn Vo Thi Ngoc Chau chauvtn@cse.hcmut.edu.vn; chauvtn@hcmut.edu.vn; chauvtn2003@gmail.com Vo Thi Ngoc Tran vtntran@hcmut.edu.vn Nguyen Duy Dat...
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References (5)

Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer Science+Business Media Dordrecht
Subject
Computer Science; Artificial Intelligence (incl. Robotics); Computer Science, general
ISSN
0269-2821
eISSN
1573-7462
DOI
10.1007/s10462-017-9538-6
Publisher site
See Article on Publisher Site

Abstract

Emotion classification is used in many commercial applications and research applications. The semantic classification models (or sentiment classification methods) are based on the vocabulary of the emotion dictionary being studied and being used very much to this day. In this study, a Vietnamese sentiment dictionary includes Vietnamese terms (Vietnamese nouns, Vietnamese verbs, Vietnamese adjectives, etc.) which the valences (and polarities) are calculated by using Ochiai measure through Google search engine and many Vietnamese adjective phrases which the valences (and polarities) are identified based on Vietnamese language characteristics. The Vietnamese adjectives often bear emotion which values (or semantic scores) are not fixed and are changed when they appear in different contexts of these phrases. Therefore, if the Vietnamese adjectives bring sentiment and their semantic values (or their sentiment scores) are not changed in any context, then the results of the emotion classification are not high accuracy. We propose many rules based on Vietnamese language characteristics to determine the emotional values of the Vietnamese adjective phrases bearing sentiment in specific contexts. Our Vietnamese sentiment adjective dictionary is widely used in applications and researches of the Vietnamese semantic classification.

Journal

Artificial Intelligence ReviewSpringer Journals

Published: Jan 27, 2017

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