Enhancing Community Detection in Social Network using Ontology

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.