MuLSA-Multi Linguistic Sentimental Analyzer for Kannada and Malayalam using Deep Learning

Title

MuLSA-Multi Linguistic Sentimental Analyzer for Kannada and Malayalam using Deep Learning

Creator

Thomas M.; Ca L.

Description

Natural language Processing has been always a topic of interest in artificial intelligence. Opinion mining or Sentiment Analysis is an important application of Natural language Processing. Sentiment Analysis of text is to extract the sentiments underlined in the text. In this paper, a multi-linguistic sentimental analyzer (MuLSA), is implemented, a model that would address Malayalam, Kannada and English text. This model explores two languages in three categories of the text, its original script, transliterated script, and the combination of both along with English. Deep Learning, Recurrent Neural Network with LSTM is used as the basis for this model. The model exhibits 82% of prediction accuracy. 2021 IEEE.

Source

Proceedings of the 2021 2nd International Conference on Communication, Computing and Industry 4.0, C2I4 2021

Date

2021-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

LSTM; Natural language Processing; RNN; Sentiment Analysis

Coverage

Thomas M., CHRIST (Deemed to Be University), Department of CSE, India; Ca L., RVITM, Visvesvaraya Technological University, India

Rights

Restricted Access

Relation

ISBN: 978-166542013-6

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/C2I454156.2021.9689301

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