Enhancing Deep Learning Approach for Tamil English Mixed Text Classification

DOI

10.2991/978-94-6463-136-4_73How to use a DOI?

Keywords

BERT; CNN; Multilingual mask model

Abstract

Text Classification with sentiments understanding is an essential task for data processing and predicting user behavior. In case of Multilingual data, the process requires to convert the entire data to machine understandable language or to pre-process the text prior to classification keeping the semantics of the text intact. Deep Learning libraries like Bidirectional Encoder Representations from Transformers (BERT) with word2vector model and Convolutional Neural Network (CNN) for natural language processing (NLP) support both techniques, and the manuscript attempts to enhance pre-processing of the Tamil English Mixed text Classification. The pre-processing of the Tamil English Mixed text addressed the issue of annotated text non-availability.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Neeraj Bhargava
AU  - Anantika Johari
PY  - 2023
DA  - 2023/05/01
TI  - Enhancing Deep Learning Approach for Tamil English Mixed Text Classification
BT  - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
PB  - Atlantis Press
SP  - 829
EP  - 837
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-136-4_73
DO  - 10.2991/978-94-6463-136-4_73
ID  - Bhargava2023
ER  -