A survey on text classification algorithms: From text to predictions
In recent years, the exponential growth of digital documents has been met by rapid progress
in text classification techniques. Newly proposed machine learning algorithms leverage the …
in text classification techniques. Newly proposed machine learning algorithms leverage the …
Twenty years of machine-learning-based text classification: A systematic review
A Palanivinayagam, CZ El-Bayeh, R Damaševičius - Algorithms, 2023 - mdpi.com
Machine-learning-based text classification is one of the leading research areas and has a
wide range of applications, which include spam detection, hate speech identification …
wide range of applications, which include spam detection, hate speech identification …
A new hybrid based on long short-term memory network with spotted hyena optimization algorithm for multi-label text classification
H Khataei Maragheh, FS Gharehchopogh… - Mathematics, 2022 - mdpi.com
An essential work in natural language processing is the Multi-Label Text Classification
(MLTC). The purpose of the MLTC is to assign multiple labels to each document. Traditional …
(MLTC). The purpose of the MLTC is to assign multiple labels to each document. Traditional …
TextConvoNet: a convolutional neural network based architecture for text classification
This paper presents, TextConvoNet, a novel Convolutional Neural Network (CNN) based
architecture for binary and multi-class text classification problems. Most of the existing CNN …
architecture for binary and multi-class text classification problems. Most of the existing CNN …
Correlation analysis and text classification of chemical accident cases based on word embedding
Accident precursors can provide valuable clues for risk assessment and risk warning.
Trends such as the main characteristics, common causes, and high-frequency types of …
Trends such as the main characteristics, common causes, and high-frequency types of …
SHO-CNN: A metaheuristic optimization of a convolutional neural network for multi-label news classification
News media always pursue informing the public at large. It is impossible to overestimate the
significance of understanding the semantics of news coverage. Traditionally, a news text is …
significance of understanding the semantics of news coverage. Traditionally, a news text is …
Heuristics for online three-dimensional packing problems and algorithm selection framework for semi-online with full look-ahead
In online three-dimensional packing problems (3D-PPs), unlike offline problems, items arrive
sequentially and require immediate packing decisions without any information about the …
sequentially and require immediate packing decisions without any information about the …
[HTML][HTML] Attention-based contextual local and global features for urgent posts classification in MOOCs discussion forums
Abstract The Massive Open Online Courses (MOOCs) platform offers communication
channels for students to share concerns about the educational process. Due to the large …
channels for students to share concerns about the educational process. Due to the large …
Medical text classification based on the discriminative pre-training model and prompt-tuning
Y Wang, Y Wang, Z Peng, F Zhang, L Zhou… - Digital …, 2023 - journals.sagepub.com
Medical text classification, as a fundamental medical natural language processing task, aims
to identify the categories to which a short medical text belongs. Current research has …
to identify the categories to which a short medical text belongs. Current research has …
MCICT: Graph convolutional network-based end-to-end model for multi-label classification of imbalanced clinical text
Y He, Q Xiong, 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 …