Ontology Based Recommender System Using Social Network Data

• Post by: eargadmin
• 25 June 2021
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Abstract

Online Social Network (OSN) is considered a key source of information for real-time decision making. However, several constraints lead to decreasing the amount of information that a researcher can have while increasing the time of social network mining procedures. In this context, this paper proposes a new framework for sampling Online Social Network (OSN). Domain knowledge is used to define tailored strategies that can decrease the budget and time required for mining while increasing the recall. An ontology supports our filtering layer in evaluating the relatedness of nodes. Our approach demonstrates that the same mechanism can be advanced to prompt recommendations to users. We broke our experiments into two sets, testing on data generated randomly and others collected from Twitter. Our test cases and experimental results emphasize the importance of the strategy definition step and the application of ontologies on the knowledge graph.