The central theoretical criteria of Topic Maps “One Topic for one Subject” leads to serious problems if two distributed Topic Maps are merged: according to existing standards, two Topics will only be merged if the description of their Subejct (i.e. their so-called Subject Indentifier or Subject Locator) is exactly identical. On the other hand - from a philosophical point of view - two Topics should be merged if they describe the same Subject, i.e. if they are intended to refer to the same thing o idea.

In distributed environments, however, Topic Map authors are not always able to us a common vocabulary: in these cases they will fail to use identical Subjects Identifiers/Locators even if they intend to describe the same Subject. Therefore, we propose the SIM (Subject Identity Measure) approach which is based on a statistics using different Topic characteristics. This approach is on the one hand independent of the languages used and on the other hand of the sturcture in these Topic Maps.