Title
Building Ontology For Different Emotional Contexts And Multilingual Environment In Opinion Mining
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 Protege by using OWL2.
Year
DOI
Venue
2016
10.1080/10798587.2016.1267243
INTELLIGENT AUTOMATION AND SOFT COMPUTING
Keywords
Field
DocType
Ontology, opinion mining, social media, emotional context, multilingual environment, OWL
Ontology (information science),Ontology,Ontology-based data integration,World Wide Web,Process ontology,Sentiment analysis,Computer science,Upper ontology,Big data,Semantics
Conference
Volume
Issue
ISSN
24
1
1079-8587
Citations 
PageRank 
References 
0
0.34
2
Authors
3
Name
Order
Citations
PageRank
Wan Tao111.02
Tao Liu245.54
Wei Yu312519.50