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Automatic Extraction of Topic Maps based Argumentation Trails

Presentation, was published by Benjamin Bock, Lutz Maicher, Marco Büchler, and Frederik Baumgardt at 2009-03-25

An argumentation trail between two terms is an ordered list of cooccurrences, providing a connected path from the origin to the endpoint of the argumentation. These trails are represented as topic maps.

With argumentation trails we introduce an approach of finding relevant associations between arbitrary terms. An argumentation trail between two terms is an ordered list of cooccurrences, providing a connected path from the origin to the endpoint of the argumentation. Within this paper the automatic generation of argumentation trails is examined and assessed. Furthermore, the formal representation of these trails as Topic Maps is implemented. This enables the integration of argumentation trails with further background information to support sensemaking or other discourse enriching techniques for academic or political debates.

Publish at Scribd or explore others: Research topic maps Text Mining

Presentation held at the TMS 2009 conference.

View more presentations from Lutz Maicher.
 

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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
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Topic Maps Lab auf der Cebit 2011
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