Shifting semantic values of English phrases for classification

Shifting semantic values of English phrases for classification The researches of semantics (positive, negative, neutral) are performed for a long time and they are very important for many commercial applications, many scientific works, etc. In this paper we propose a new model to calculate the emotional values (or semantic scores) of English terms (English verbs, English nouns, English adjectives, English adverbs, etc.) as follows: firstly, we create our basis English emotional dictionary (called bEED) by using Sorensen measure (Sorensen coefficient, called SM) through Google search engine with AND operator and OR operator and secondly, many English adjective phrases, English adverb phrases and English verb phrases are created based on the English grammars (the English characteristics) by combining the English adverbs of degree with the English adjectives, the English adverbs and English verbs; finally, the valences of the English adverb phrases are identified by their specific contexts. The English phrases often bring the semantics which the values (or emotional scores) are not fixed and are changed when they appear in their different contexts. Therefore, the results of the sentiment classification are not high accuracy if the English phrases bring the emotions and their semantic values (or their sentiment scores) are not changed in any context. For those reasons, we propose many rules based on English language grammars to calculate the sentimental values of the English phrases bearing emotion in their specific contexts. The results of this work are widely used in applications and researches of the English semantic classification. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Speech Technology Springer Journals

Shifting semantic values of English phrases for classification

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Publisher
Springer US
Copyright
Copyright © 2017 by Springer Science+Business Media New York
Subject
Engineering; Signal,Image and Speech Processing; Social Sciences, general; Artificial Intelligence (incl. Robotics)
ISSN
1381-2416
eISSN
1572-8110
D.O.I.
10.1007/s10772-017-9420-6
Publisher site
See Article on Publisher Site

Abstract

The researches of semantics (positive, negative, neutral) are performed for a long time and they are very important for many commercial applications, many scientific works, etc. In this paper we propose a new model to calculate the emotional values (or semantic scores) of English terms (English verbs, English nouns, English adjectives, English adverbs, etc.) as follows: firstly, we create our basis English emotional dictionary (called bEED) by using Sorensen measure (Sorensen coefficient, called SM) through Google search engine with AND operator and OR operator and secondly, many English adjective phrases, English adverb phrases and English verb phrases are created based on the English grammars (the English characteristics) by combining the English adverbs of degree with the English adjectives, the English adverbs and English verbs; finally, the valences of the English adverb phrases are identified by their specific contexts. The English phrases often bring the semantics which the values (or emotional scores) are not fixed and are changed when they appear in their different contexts. Therefore, the results of the sentiment classification are not high accuracy if the English phrases bring the emotions and their semantic values (or their sentiment scores) are not changed in any context. For those reasons, we propose many rules based on English language grammars to calculate the sentimental values of the English phrases bearing emotion in their specific contexts. The results of this work are widely used in applications and researches of the English semantic classification.

Journal

International Journal of Speech TechnologySpringer Journals

Published: May 16, 2017

References

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