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.
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Papantoniou, K., Tsatsaronis, G., Paliouras, G. (2010). KDTA: Automated Knowledge-Driven Text Annotation. In: Balcázar, J.L., Bonchi, F., Gionis, A., Sebag, M. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2010. Lecture Notes in Computer Science(), vol 6323. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15939-8_45
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DOI: https://doi.org/10.1007/978-3-642-15939-8_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15938-1
Online ISBN: 978-3-642-15939-8
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