@inproceedings{ea133fc6be1243f3b01218fc78b2b4fc,
title = "An Automatic Text Classification Method Based on Hierarchical Taxonomies, Neural Networks and Document Embedding: The NETHIC Tool",
abstract = "This work describes an automatic text classification method implemented in a software tool called NETHIC, which takes advantage of the inner capabilities of highly-scalable neural networks combined with the expressiveness of hierarchical taxonomies. As such, NETHIC succeeds in bringing about a mechanism for text classification that proves to be significantly effective as well as efficient. The tool had undergone an experimentation process against both a generic and a domain-specific corpus, outputting promising results. On the basis of this experimentation, NETHIC has been now further refined and extended by adding a document embedding mechanism, which has shown improvements in terms of performance on the individual networks and on the whole hierarchical model.",
keywords = "Document embedding, Machine learning, Neural networks, Taxonomies, Text classification, Document embedding, Machine learning, Neural networks, Taxonomies, Text classification",
author = "Luigi Lomasto and {Di Florio}, Rosario and Andrea Ciapetti and Giuseppe Miscione and Giulia Ruggiero and Daniele Toti",
year = "2020",
doi = "10.1007/978-3-030-40783-4_4",
language = "English",
isbn = "978-3-030-40782-7",
volume = "378",
series = "LECTURE NOTES IN BUSINESS INFORMATION PROCESSING",
pages = "57--77",
booktitle = "Lecture Notes in Business Information Processing",
note = "21st International Conference on Enterprise Information Systems, ICEIS 2019 ; Conference date: 03-05-2019 Through 05-05-2019",
}