Open AccessProceedings Article
CREAM: creating relational metadata with a component-based, ontology-driven annotation framework
Siegfried Handschuh,Steffen Staab,Alexander Maedche +2 more
- pp 515-528
TLDR
CREAM (Creating RElational, Annotation-based Metadata), a framework for an annotation environment that allows to construct relational metadata, i.e. metadata that comprises class instances and relationship instances, is presented.Abstract:
Richly interlinked, machine-understandable data constitutes the basis for the Semantic Web. Annotating web documents is one of the major techniques for creating metadata on the Web. However, annotation tools so far are restricted in their capabilities of providing richly interlinked and truely machine-understandable data. They basically allow the user to annotate with plain text according to a template structure, such as Dublin Core. We here present CREAM (Creating RElational, Annotation-based Metadata), a framework for an annotation environment that allows to construct relational metadata, i.e. metadata that comprises class instances and relationship instances. These instances are not based on a fix structure, but on a domain ontology. We discuss some of the requirements one has to meet when developing such a framework, e.g. the integration of a metadata crawler, inference services, document management and information extraction, and describe its implementation, viz. Ont-O-Mat a component-based, ontology-driven annotation tool.read more
Citations
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EDUTELLA: a P2P networking infrastructure based on RDF
Wolfgang Nejdl,Boris Wolf,Changtao Qu,Stefan Decker,Michael Sintek,Ambjörn Naeve,Mikael Nilsson,Matthias Palmér,Tore Risch +8 more
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Towards the self-annotating web
TL;DR: PANKOW (Pattern-based Annotation through Knowledge on theWeb), a method which employs an unsupervised, pattern-based approach to categorize instances with regard to an ontology, is proposed.
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S-CREAM - Semi-automatic CREAtion of Metadata
TL;DR: OntoMat-Annotizer extract with the help of Amilcare knowledge structure from web pages through the use of knowledge extraction rules, the result of a learning-cycle based on already annotated pages.
Book ChapterDOI
MnM: Ontology Driven Semi-automatic and Automatic Support for Semantic Markup
TL;DR: M is presented, an annotation tool which provides both automated and semi-automated support for annotating web pages with semantic contents and integrates a web browser with an ontology editor and provides open APIs to link to ontology servers and for integrating information extraction tools.
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