Enhancing Community Detection in Social Network using Ontology

Salma Khattab, Abeer ElKorany, Akram Salah

Abstract

In recent years, social networks have been spread widely. Within social network, people tend to form communities in order to have more chances to share opinions, experiences and expertise. Users in social networks belong to the same community according to their behaviour and common interest. This paper presents a semantic approach for community extraction based on identifying the interest of user in order to group them into communities. An ontological user profile is created indicating user interest that is associated with items domain ontology. A set of experiments was applied using real dataset (BookCrossing) to measure the accuracy of the proposed semantic-based framework.

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Paper Citation


in Harvard Style

Khattab S., ElKorany A. and Salah A. (2016). Enhancing Community Detection in Social Network using Ontology . In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2016) ISBN 978-989-758-203-5, pages 150-156. DOI: 10.5220/0006067801500156


in Bibtex Style

@conference{keod16,
author={Salma Khattab and Abeer ElKorany and Akram Salah},
title={Enhancing Community Detection in Social Network using Ontology},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2016)},
year={2016},
pages={150-156},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006067801500156},
isbn={978-989-758-203-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2016)
TI - Enhancing Community Detection in Social Network using Ontology
SN - 978-989-758-203-5
AU - Khattab S.
AU - ElKorany A.
AU - Salah A.
PY - 2016
SP - 150
EP - 156
DO - 10.5220/0006067801500156