An Automatic Text Classification Method Based On Hierarchical Taxonomies, Neural Networks And Document Embedding: The Nethic Tool
ENTERPRISE INFORMATION SYSTEMS (ICEIS 2019)(2020)
摘要
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.
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关键词
Machine learning, Neural networks, Taxonomies, Text classification, Document embedding
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