A Novel Approach using Context Matching Algorithm and Knowledge Inference for User Identification in Social Networks

User identifications are in searching Online Social Networks (OSN) to find identical users among different social sites in many data sources (data integration, data enrichment, information retrieval,...). However, these user-unique attributes are difficult to obtain due to privacy issues. It is hard to identify users across multiple OSNs online. This paper has presented user's identification across multiple OSNs in order to develop searching engine for user identification. The proposed approach is designed to find by searching engine while accommodating User identifications in searching Online Social Networks (OSN). Experimental results demonstrate that our proposed approach achieves a significant improvement in term of performance accuracy.