Title

Text Classification Using Neural Network Language Model (NNLM) and BERT: An Empirical Comparison

Document Type

Conference Proceeding

Publication Date

1-1-2022

Publication Title

Lecture Notes in Networks and Systems

Publisher

Springer

Publisher Location

New York, NY

Volume

296

First page number:

175

Last page number:

189

Abstract

Text Classification is one of the most cited applications of Natural Language Processing. Classification can save the cost of manual efforts and at the same time increase the accuracy of a task. With multiple advancements in language modeling techniques over the last two decades, a number of word embedding models have been proposed. In this study, we discuss and compare two of the most recent models for the task text classification and present a technical comparison.

Keywords

BERT; Language model; Natural Language Processing; NLP; Text classification; Transformers; Word embedding

Disciplines

Other Computer Sciences | Programming Languages and Compilers

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