NETHIC: A System for Automatic Text Classification using Neural Networks and Hierarchical Taxonomies

Andrea Ciapetti, Rosario Di Florio, Luigi Lomasto, Giuseppe Miscione, Giulia Ruggiero, Daniele Toti

Abstract

This paper presents NETHIC, a software system for the automatic classification of textual documents based on hierarchical taxonomies and artificial neural networks. This approach combines the advantages of highly-structured hierarchies of textual labels with the versatility and scalability of neural networks, thus bringing about a textual classifier that displays high levels of performance in terms of both effectiveness and efficiency. The system has first been tested as a general-purpose classifier on a generic document corpus, and then applied to the specific domain tackled by DANTE, a European project that is meant to address criminal and terrorist-related online contents, showing consistent results across both application domains.

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Paper Citation


in Harvard Style

Ciapetti A., Di Florio R., Lomasto L., Miscione G., Ruggiero G. and Toti D. (2019). NETHIC: A System for Automatic Text Classification using Neural Networks and Hierarchical Taxonomies.In Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-372-8, pages 296-306. DOI: 10.5220/0007709702960306


in Bibtex Style

@conference{iceis19,
author={Andrea Ciapetti and Rosario Di Florio and Luigi Lomasto and Giuseppe Miscione and Giulia Ruggiero and Daniele Toti},
title={NETHIC: A System for Automatic Text Classification using Neural Networks and Hierarchical Taxonomies},
booktitle={Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2019},
pages={296-306},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007709702960306},
isbn={978-989-758-372-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - NETHIC: A System for Automatic Text Classification using Neural Networks and Hierarchical Taxonomies
SN - 978-989-758-372-8
AU - Ciapetti A.
AU - Di Florio R.
AU - Lomasto L.
AU - Miscione G.
AU - Ruggiero G.
AU - Toti D.
PY - 2019
SP - 296
EP - 306
DO - 10.5220/0007709702960306