KDTA: Automated Knowledge-Driven Text Annotation
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.
Cite
Text
Papantoniou et al. "KDTA: Automated Knowledge-Driven Text Annotation." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2010. doi:10.1007/978-3-642-15939-8_45Markdown
[Papantoniou et al. "KDTA: Automated Knowledge-Driven Text Annotation." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2010.](https://mlanthology.org/ecmlpkdd/2010/papantoniou2010ecmlpkdd-kdta/) doi:10.1007/978-3-642-15939-8_45BibTeX
@inproceedings{papantoniou2010ecmlpkdd-kdta,
title = {{KDTA: Automated Knowledge-Driven Text Annotation}},
author = {Papantoniou, Katerina and Tsatsaronis, George and Paliouras, Georgios},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2010},
pages = {611-614},
doi = {10.1007/978-3-642-15939-8_45},
url = {https://mlanthology.org/ecmlpkdd/2010/papantoniou2010ecmlpkdd-kdta/}
}