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Authors: Samreen Zehra ; Shaukat Wasi ; Imran Jami ; Aisha Nazir ; Ambreen Khan and Nusrat Waheed

Affiliation: Mohammad Ali Jinnah University, Pakistan

Keyword(s): Ontology, Sentiment Analysis, Recommendation System.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Domain Analysis and Modeling ; Enterprise Information Systems ; Expert Systems ; Health Engineering and Technology Applications ; Health Information Systems ; Information Systems Analysis and Specification ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Natural Language Processing ; Ontologies and the Semantic Web ; Ontology Engineering ; Pattern Recognition ; Symbolic Systems

Abstract: In this paper, we propose a novel approach towards developing a recommendation system using ontology-based sentiment analysis. To conduct our study, we have targeted a Facebook closed group which contains posts/reviews regarding different schools. For elucidating the knowledge domain, a school ontology is manually designed based on a set of extracted post/comment data. Sentiment analysis is consequently performed on the resulting Data set and the relative sentiment scores are stored back in the ontology for making recommendations in future.

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Paper citation in several formats:
Zehra, S.; Wasi, S.; Jami, I.; Nazir, A.; Khan, A. and Waheed, N. (2017). Ontology-based Sentiment Analysis Model for Recommendation Systems. In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KEOD; ISBN 978-989-758-272-1; ISSN 2184-3228, SciTePress, pages 155-160. DOI: 10.5220/0006491101550160

@conference{keod17,
author={Samreen Zehra. and Shaukat Wasi. and Imran Jami. and Aisha Nazir. and Ambreen Khan. and Nusrat Waheed.},
title={Ontology-based Sentiment Analysis Model for Recommendation Systems},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KEOD},
year={2017},
pages={155-160},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006491101550160},
isbn={978-989-758-272-1},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KEOD
TI - Ontology-based Sentiment Analysis Model for Recommendation Systems
SN - 978-989-758-272-1
IS - 2184-3228
AU - Zehra, S.
AU - Wasi, S.
AU - Jami, I.
AU - Nazir, A.
AU - Khan, A.
AU - Waheed, N.
PY - 2017
SP - 155
EP - 160
DO - 10.5220/0006491101550160
PB - SciTePress

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