Subject Identification in Topic Maps in Theory and Practice

If Topic Maps should be exchanged in distributed environments a common semantic problem occurs: Do two Topics refer to the same Subject? If they describe the same Subject the given Topics have to be treated as one unit in the given context. Especially in integration scenarios this might be important. Within the Topic Map theory the merging paradigm and the description of Subjects of discourse is the central design criterion. These methods provided by the standard lead to sufficient results, but only if two distributed Topic Map authors share the same vocabulary for Subject description. But in our current research with automatic generated, hand-crafted refined Topic Maps we have to handle heterogeneous vocabularies. To solve the arising problems we introduced the Subject Identity Measure (SIM) which describes how closely related the Subjects of two distributed Topics are. In the context of the doctoral consortium on the one hand we want to show how the omnipresent problem of Subject Identification is solved in the Topic Map theory, including the attendant shortcomings. On the other hand we want to discuss how our solution of automatic Subject comparison can be enhanced (with experiences from related technologies) and how our solution can be used to integrate the Topic Map world with other XML technologies based on the merging paradigm.