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Merging of Distributed Topic Maps based on the Subject Identity Measure

Paper, was published by Lutz Maicher and Hans Friedrich Witschel at 2004-09-30

This paper proposes the Subject Identifier Measure approach which is based on a statistics using different Topic characteristics.

External Link: download paper

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.

 

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As a former information scientist, I am fascinated since 1999 by the capabilities for building Topic Maps-based knowledge systems having the potential to augment human mind. One can model arbitrary knowledge organization systems, deal with semantic heterogeneity, collocate all facts about one subject in one logical place, and with TMQL have semantic retrieval on federated semantic networks. Therefore I expect bright prospects for business concepts building on the exchange of such knowledge snippets via semantic knowledge services.

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Alexander Sigel
practical-semantics.com
Topic Maps Lab auf der Cebit 2011
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