SemFus: Semantic fusion framework based on JDL

Abstract

Data fusion techniques combine data from multiple sources and gather related information to achieve more specific inferences than could be achieved by using a single source. The most widely-used method for categorizing data fusion-related functions is the JDL model, but it suffers from semantics and syntax issues. In order to achieve semantic interoperability in a heterogeneous information system, the meaning of the information that is interchanged has to be understood across the systems. Semantic conflicts occur whenever two contexts do not use the same interpretation of the information. Using semantic technologies for the extraction of implicit knowledge is a new approach to overcome this problem. In this paper a semantic fusion framework (SemFus) is proposed based on JDL which can overcome the semantic problems in heterogeneous systems. © 2013 Springer Science+Business Media.