A Link-based Approach to Entity Resolution in Social Networks
This addresses the challenge of efficient information retrieval in social networks for users and analysts, though it appears incremental in extending existing methodologies.
The paper tackles the problem of accurately resolving duplicate entities in social networks to improve information retrieval, proposing a novel link-based approach that extends entity resolution to multitype problems and is validated through comprehensive evaluation.
Social networks initially had been places for people to contact each other, find friends or new acquaintances. As such they ever proved interesting for machine aided analysis. Recent developments, however, pivoted social networks to being among the main fields of information exchange, opinion expression and debate. As a result there is growing interest in both analyzing and integrating social network services. In this environment efficient information retrieval is hindered by the vast amount and varying quality of the user-generated content. Guiding users to relevant information is a valuable service and also a difficult task, where a crucial part of the process is accurately resolving duplicate entities to real-world ones. In this paper we propose a novel approach that utilizes the principles of link mining to successfully extend the methodology of entity resolution to multitype problems. The proposed method is presented using an illustrative social network-based real-world example and validated by comprehensive evaluation of the results.