Ontology Reasoning Towards Sentimental Product Recommendations Explanations
Vidya Kamma1 , Teja Santosh Dandibhotla2, Sridevi Gutta3

1Vidya Kamma, Research Scholar ,K L (Deemed to be University), Andhra Pradesh State,India and Assistant Professor,Neil Gogte Institute of Technology, Hyderabad, Telangana, India.
2Teja Santosh Dandibhotla, Associate Professor,Sreenidhi Institute of Science and Technology Yamnampet, Ghatkesar, Telangana , India.
3Sridevi Gutta , Professor,K L (Deemed to be University), Andhra Pradesh , India.

Manuscript received on 05 August 2019. | Revised Manuscript received on 14 August 2019. | Manuscript published on 30 September 2019. | PP: 4706-4709 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6852098319/2019©BEIESP | DOI: 10.35940/ijrte.C6852.098319
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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 the last two decades various organizations like service industries, study communities, academic world and public industries are working intensely on sentiment analysis, to extract and analyze public views. The reviews given on the social websites, commercial websites, etc. enable customer to share their point of view. Explainable Recommendation algorithms help the user by providing explainable recommendations, which improves user satisfaction. Recently, many researchers proposed explainable recommendations. In this survey Firstly, various opinion-mining approaches are explored. Secondly, we reviewed sentiment-based and ontology based recommendation systems. Finally, prospects for the research in opinion mining is discussed.
Keywords: Opinion Mining, Opinion Orientation, Ontology, Product Features, Sentiment.

Scope of the Article:
Reasoning and Inference