Research Area:  Machine Learning
Text classification is one of the fundamental problems in Natural Language Processing (NLP). Several research studies have used deep learning approaches such as Convolution Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) for text classification. Over the past decade, graph-based approaches have been used to solve various NLP tasks including text classification. This paper reviews the most recent state-of-the-art graph-based text classification, datasets, and performance evaluations versus baseline models.
Author(s) Name:  Masoud Malekzadeh; Parisa Hajibabaee; Maryam Heidari; Samira Zad; Ozlem Uzuner; James H Jones
Conferrence name:  IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)
Publisher name:  IEEE
Paper Link:   https://ieeexplore.ieee.org/abstract/document/9666633