The reusability of induced knowledge for the automatic semantic markup of taxonomic descriptions

To automatically convert legacy data of taxonomic descriptions into extensible markup language (XML) format, the authors designed a machine‐learning‐based approach. In this project three corpora of taxonomic descriptions were selected to prove the hypothesis that domain knowledge and conventions aut...

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Vydáno v:	Journal of the American Society for Information Science and Technology Ročník 58; číslo 1; s. 133 - 149
Hlavní autoři:	Cui, Hong, Heidorn, P. Bryan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.01.2007 Wiley Wiley Periodicals Inc
Témata:	Automatic classification Classification Content analysis Conventions Descriptions Document markup languages Exact sciences and technology Experiments Extensible Markup Language Formats. Codification. Conversion Formats. Markup languages. Codification. Conversion Indexing. Classification. Abstracting Indexing. Classification. Abstracting. Syntheses Induced Information and communication sciences Information and document structure and analysis Information processing and retrieval Information science. Documentation Knowledge Knowledge management Machine learning N-Gram language models Performance evaluation Sciences and techniques of general use Semantic analysis Semantics Semiotics Studies Taxonomy Text segmentation Training Treatment methods XML Performance evaluation Description language Semantic analysis Taxonomy Syntactic analysis XML language Knowledge base Algorithm Knowledge Knowledge extraction Automatic processing Flora Document structure Machine learning Markup
ISSN:	1532-2882, 2330-1635, 1532-2890, 2330-1643
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