@Article{10798587.2016.1267243,
AUTHOR = {Wan Tao, Tao Liu},
TITLE = {Building Ontology for Different Emotional Contexts and Multilingual Environment in Opinion Mining},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {24},
YEAR = {2018},
NUMBER = {1},
PAGES = {65--72},
URL = {http://www.techscience.com/iasc/v24n1/39726},
ISSN = {2326-005X},
ABSTRACT = {With the explosive growth of various social media applications, individuals and organizations are 
increasingly using their contents (e.g. reviews, forum discussions, blogs, micro-blogs, comments, and 
postings in social network sites) for decision-making. These contents are typical big data. Opinion 
mining or sentiment analysis focuses on how to extract emotional semantics from these big data to help 
users to get a better decision. That is not an easy task, because it faces many problems, such as different 
context may make the meaning of the same word change variously, at the same time multilingual 
environment restricts the full use of the analysis results. Ontology provides knowledge about specific 
domains that are understandable by both the computers and developers. Building ontology is mainly a 
useful first step in providing and formalizing the semantics of information representation. We proposed 
an ontology DEMLOnto based on six basic emotions to help users to share existed information. The 
ontology DEMLOnto would help in identifying the opinion features associated with the contextual 
environment, which may change along with applications. We built the ontology according to ontology 
engineering. It was developed on the platform Protégé by using OWL2.},
DOI = {10.1080/10798587.2016.1267243}
}