KDTA: automated knowledge-driven text annotation

Authors:
Katerina Papantoniou;George Tsatsaronis;Georgios Paliouras
Affiliations:
Institute of Informatics Telecommunications, NCSR "Demokritos", Greece;Dept. of Computer and Information Science, Norwegian University of Science and Technology;Institute of Informatics Telecommunications, NCSR "Demokritos", Greece
Venue:
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Year:
2010

Citing 4
Cited 1

Gimme' the context: context-driven automatic semantic annotation with C-PANKOW

WWW '05 Proceedings of the 14th international conference on World Wide Web
Ontology based annotation of text segments

Proceedings of the 2007 ACM symposium on Applied computing
Text relatedness based on a word thesaurus

Journal of Artificial Intelligence Research
Scalable semantic annotation of text using lexical and web resources

SETN'10 Proceedings of the 6th Hellenic conference on Artificial Intelligence: theories, models and applications

Towards ABox Modularization of semi-expressive Description Logics

Applied Ontology - Modularity in Ontologies

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we demonstrate a system that automatically annotates text documents with a given domain ontology's concepts. The annotation process utilizes lexical and Web resources to analyze the semantic similarity of text components with any of the ontology concepts, and outputs a list with the proposed annotations, accompanied with appropriate confidence values. The demonstrated system is available online and free to use, and it constitutes one of the main components of the KDTA (Knowledge-Driven Text Analysis) module of the CASAM European research project.