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Subject Identification in Topic Maps in Theory and Practice

Paper, was published by Lutz Maicher at 2004-10-13

This paper introduces the Subject Identity Measure.

External Link: download paper

If Topic Maps should be exchanged in distributed environments a common semantic problem occurs: Do two Topics represent the same Subject? If they describe the same Subject the according Topics have to be merged. Within the Topic Map theory the merging paradigm and the description of Subjects is the main theoretical design criterion. Normally, these methods provided by the standard lead to sufficient results, but only if distributed Topic Map authors share a common vocabulary for Subject description. To solve the arising problems for distributed, autonomous environments we introduce the Subject Identity Measure. The SIM describes how closely related the Subjects of two distributed Topics are. The approach is independent from a shared vocabulary, from a specific natural languages and uses only data which is available inside the according Topic Maps.


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Nowadays Topic Maps appears to be very suitable for being applied in Libraries, Archives and Museums. It provides a suitable model and mechanisms for depth indexing, classification and the implementation of FRBR, CIDOC-CRM or other conceptualizations.

Liliana Melgar
Topic Maps Lab auf der Cebit 2011

Graduate from the Topic Maps Lab