  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.
