Ontology Based Method for Sentiment Examination
Puninder Kaur1, Ruchi Mittal2
1Puninder Kaur, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India.
2Ruchi Mittal, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India.
Manuscript received on October 14, 2019. | Revised Manuscript received on 22 October, 2019. | Manuscript published on November 10, 2019. | PP: 5198-5202 | Volume-9 Issue-1, November 2019. | Retrieval Number: A9231119119/2019©BEIESP | DOI: 10.35940/ijitee.A9231.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In recent years, sentiment analysis became an important concept which is used to extract an important feature or text mining according to our interest. It is very difficult to judge the polarity or the review of particular product. This problem is solved by ontology. Ontology is a formal and shared specification of a particular domain. It is a large semantic network used to extract a domain specific concept or domain specific features of a particular product. Ontology contains concept which means domain and sets of objects or we can say instance of concept and relationship between various objects. Ontology based approach is classification of opinion and feature-based approach. Ontology gives domain specific features along with the hieratical relationship between them. Ontology generates semantic graphs and tree for showing relationship between different domains and entities. The relationship can be done on the basis of nodes and edges connections. We use some contextual lexicons which are used to provide the opinion about particular domain like SentiWordNet, SenticNet, WordNet etc. This survey aims to provide an insight on Opinion target, Opinion lexical and Aspect based Polarity detection, sentiment aggregation.
Keywords: Ontology, Aspect Level Polarity, Semantic Network, Senti WordNet, Sentic Net, Sentiment Analysis.
Scope of the Article: Classification