Reasoning about Social Semantic Web Applications using String Similarity and Frame Logic

Social semantic Web or Web 3.0 application 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 metrics 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 metric yields surprisingly good results on Croatian words and phrases

Towards a General Definition of Biometric Systems

A foundation for closing the gap between biometrics in the narrower and the broader perspective is presented trough a conceptualization of biometric systems in both perspectives. A clear distinction between verification, identification and classification systems is made as well as shown that there are additional classes of biometric systems. In the end a Unified Modeling Language model is developed showing the connections between the two perspectives