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  4. Content management and knowledge management : two faces of ontology-based deep-level interpretation of text
 
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Content management and knowledge management : two faces of ontology-based deep-level interpretation of text

Citation Link: https://doi.org/10.15480/882.1029
Other Titles
Content Management und Knowledge Management : die zwei Schichten der logikbasierte Textinterpretation anhand von Ontologien
Publikationstyp
Doctoral Thesis
Date Issued
2011
Sprache
English
Author(s)
Espinosa Peraldi, Irma Sofia  
Advisor
Möller, Ralf  
Title Granting Institution
Technische Universität Hamburg
Place of Title Granting Institution
Hamburg
Examination Date
2011-09-16
Institut
Softwaresysteme E-16  
TORE-DOI
10.15480/882.1029
TORE-URI
http://tubdok.tub.tuhh.de/handle/11420/1031
In order to make content management systems able to exploit annotations about content semantics for the management of content, this work proposes an approach for text interpretation that is built on the principles of logic-based abduction. The approach is presented in the context of a framework that allows for a deep-level interpretation of text. The research contributions of this work encompass (1) a framework for the integration of shallow-processing techniques of text with logic-based techniques to cope with the extraction
of content descriptions that describe media contents in detail; (2) the design of a logic-based process for multimedia fusion that supports the systematic combination of interpretation results obtained from different types of media (e.g., text and image); (3) the description of design patterns for domain ontologies and rules useful for logic-based media interpretation; (4) the use of text interpretation to guide the task of ontology design (“Grounded Ontology Design") as a strategy to support knowledge management in an organization; (5) the design and implementation of an application that shows the advantages of using annotations to support location-aware and situation-specific services
as a new kind of content management.
Subjects
ontologies ; content management ; knowledge management ; text interpretation ; linked data
Lizenz
http://doku.b.tu-harburg.de/doku/lic_ohne_pod.php
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