Ontology-based Sentiment Analysis Model for Recommendation Systems

Samreen Zehra, Shaukat Wasi, Imran Jami, Aisha Nazir, Ambreen Khan, Nusrat Waheed

2017

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 Harvard Style

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 - Volume 2: KEOD, ISBN 978-989-758-272-1, pages 155-160. DOI: 10.5220/0006491101550160


in Bibtex Style

@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 - Volume 2: KEOD,},
year={2017},
pages={155-160},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006491101550160},
isbn={978-989-758-272-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD,
TI - Ontology-based Sentiment Analysis Model for Recommendation Systems
SN - 978-989-758-272-1
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