Semantic lexicons of English nouns for classification

• Published in: Evolving systems Vol. 10; no. 3; pp. 501 - 565
• Main Authors: Phu, Vo Ngoc, Tran, Vo Thi Ngoc, Chau, Vo Thi Ngoc, Duy, Dat Nguyen, Duy, Khanh Ly Doan
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2019
• Subjects: Artificial Intelligence; Complex Systems; Complexity; Engineering; Original Paper; English emotion classification; English sentiment dictionary; English noun; English language characteristic; English sentiment classification; English emotion dictionary; English grammar; English semantic classification
• ISSN: 1868-6478; 1868-6486
• DOI: 10.1007/s12530-017-9188-6

Sentiment classification is studied for a long time and there are many applications and many researches to service communities, commerce, politics, etc. In this research, 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: first of all, we build our basis English sentiment dictionary (called bESD) by using Tanimoto Coefficient (Tanimoto measure, called TC) through Google search engine with AND operator and OR operator and then, we create many English noun phrases based on the English grammars (the English characteristics) and the valences of the English noun phrases are identified by their specific contexts. The English noun 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 noun phrases bring the emotions and their semantic values (or their sentimental 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 noun phrases bearing emotion in their specific contexts. The results of this work are widely used in applications and researches of the English semantic classification.