Semantic taxonomy enrichment to improve business text classification for dynamic environments

Author:

Arslan Muhammad1,Cruz Christophe1

Affiliation:

1. Laboratoire d’Informatique de Bourgogne (LIB),Dijon,France,21000

Publisher

IEEE

Reference27 articles.

1. Enriching Word Vectors with Subword Information

2. Does BERT make any sense? Interpretable word sense disambiguation with contextualized embeddings;wiedemann,2019

3. BERT: Pre-training of deep bidirectional transformers for language understanding;devlin;Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics Human Language Technologies,2019

4. BERTopic: Neural topic modeling with a class-based TF-IDF procedure;grootendorst,2022

5. Topic models for taxonomies

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1. Business text classification with imbalanced data and moderately large label spaces for digital transformation;Applied Network Science;2024-04-30

2. Enabling Digital Transformation through Business Text Classification with Small Datasets;2023 15th International Conference on Innovations in Information Technology (IIT);2023-11-14

3. Semantic Business Trajectories Modeling and Analysis;New Trends in Database and Information Systems;2023

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