The average person today is required to create and separately manage multiple online identities in heterogeneous online accounts. Their integration would enable a single entry point for the management of a person's digital personal information. Thus, we target the extraction, retrieval and integration of these identities, using a comprehensive ontology framework serving as a standard format. A major challenge to achieve this integration is the discovery of semantic equivalence between multiple online identities (through attributes, relationships, shared posts, etc.). In this paper we outline a hybrid syntactic/semantic-based approach to online identity reconciliation. We also discuss the results of syntactic matching experiments conducted on real data, the current status of the work and our future research and development plans in this direction. © Springer-Verlag 2013.
CITATION STYLE
Cortis, K., Scerri, S., & Rivera, I. (2013). Techniques for the identification of semantically-equivalent online identities. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8194 LNCS, pp. 1–22). Springer Verlag. https://doi.org/10.1007/978-3-642-45263-5_1
Mendeley helps you to discover research relevant for your work.