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Social semantic Web or Web 3.0 applications gained major attention from academia and industry in recent times. Such applications try to take advantage of user supplied meta data, using ideas from the semantic Web initiative, in order to provide better services. An open problem is the formalization of such meta data, due to its complex and often inconsistent nature. A possible solution to inconsistencies are string similarity measures which are explained and analyzed. A study of performance and applicability in a frame logic environment is conducted on the case of agent reasoning about multiple domains in TaOPis -- a social semantic Web application for self-organizing communities. Results show that the NYSIIS measure yields suprisingly good results on Croatian words and phrases.