Review of graph neural network in text classification
M Malekzadeh, P Hajibabaee, M Heidari… - 2021 IEEE 12th …, 2021 - ieeexplore.ieee.org
Text classification is one of the fundamental problems in Natural Language Processing
(NLP). Several research studies have used deep learning approaches such as Convolution …
(NLP). Several research studies have used deep learning approaches such as Convolution …
ML-Net: multi-label classification of biomedical texts with deep neural networks
Objective In multi-label text classification, each textual document is assigned 1 or more
labels. As an important task that has broad applications in biomedicine, a number of different …
labels. As an important task that has broad applications in biomedicine, a number of different …
Deep neural network for hierarchical extreme multi-label text classification
The classification of natural language texts has gained a growing importance in many real
world applications due to its significant implications in relation to crucial tasks, such as …
world applications due to its significant implications in relation to crucial tasks, such as …
GeoAI in social science
W Li - Handbook of Spatial Analysis in the Social Sciences, 2022 - elgaronline.com
GeoAI, or geospatial artificial intelligence, is an exciting new area that leverages artificial
intelligence (AI), geospatial big data and massive computing power to solve problems in …
intelligence (AI), geospatial big data and massive computing power to solve problems in …
[HTML][HTML] GHS-NET a generic hybridized shallow neural network for multi-label biomedical text classification
Exponential growth of biomedical literature and clinical data demands more robust yet
precise computational methodologies to extract useful insights from biomedical literature …
precise computational methodologies to extract useful insights from biomedical literature …
Lightweight Multireceptive Field CNN for 12‐Lead ECG Signal Classification
The electrical activity produced during the heartbeat is measured and recorded by an ECG.
Cardiologists can interpret the ECG machine's signals and determine the heart's health …
Cardiologists can interpret the ECG machine's signals and determine the heart's health …
MCICT: Graph convolutional network-based end-to-end model for multi-label classification of imbalanced clinical text
Y He, Q **ong, C Ke, Y Wang, Z Yang, H Yi… - … Signal Processing and …, 2024 - Elsevier
The rapid growth of clinical text data requires accurate and powerful automated
classification methods to support medical decision making and personalized healthcare …
classification methods to support medical decision making and personalized healthcare …
Multi-class railway complaints categorization using Neural Networks: RailNeural
Indian railways are one of the largest rail networks in the world, and millions of passengers
travel daily through it, due to which there are also a vast number of complaints in front of …
travel daily through it, due to which there are also a vast number of complaints in front of …
MLR-predictor: a versatile and efficient computational framework for multi-label requirements classification
Introduction Requirements classification is an essential task for development of a successful
software by incorporating all relevant aspects of users' needs. Additionally, it aids in the …
software by incorporating all relevant aspects of users' needs. Additionally, it aids in the …
[HTML][HTML] Exploring Sentiment Analysis for the Indonesian Presidential Election Through Online Reviews Using Multi-Label Classification with a Deep Learning …
AN Ma'aly, D Pramesti, AD Fathurahman… - Information, 2024 - mdpi.com
Presidential elections are an important political event that often trigger intense debate. With
more than 139 million users, YouTube serves as a significant platform for understanding …
more than 139 million users, YouTube serves as a significant platform for understanding …