[HTML][HTML] A survey on deep learning for textual emotion analysis in social networks

S Peng, L Cao, Y Zhou, Z Ouyang, A Yang, X Li… - Digital Communications …, 2022‏ - Elsevier
Abstract Textual Emotion Analysis (TEA) aims to extract and analyze user emotional states
in texts. Various Deep Learning (DL) methods have developed rapidly, and they have …

[HTML][HTML] Learning from imbalanced data: open challenges and future directions

B Krawczyk - Progress in artificial intelligence, 2016‏ - Springer
Despite more than two decades of continuous development learning from imbalanced data
is still a focus of intense research. Starting as a problem of skewed distributions of binary …

A review on classification of imbalanced data for wireless sensor networks

H Patel, D Singh Rajput… - International …, 2020‏ - journals.sagepub.com
Classification of imbalanced data is a vastly explored issue of the last and present decade
and still keeps the same importance because data are an essential term today and it …

K-EmoCon, a multimodal sensor dataset for continuous emotion recognition in naturalistic conversations

CY Park, N Cha, S Kang, A Kim, AH Khandoker… - Scientific Data, 2020‏ - nature.com
Recognizing emotions during social interactions has many potential applications with the
popularization of low-cost mobile sensors, but a challenge remains with the lack of …

Data oversampling and imbalanced datasets: An investigation of performance for machine learning and feature engineering

M Mujahid, E Kına, F Rustam, MG Villar, ES Alvarado… - Journal of Big Data, 2024‏ - Springer
The classification of imbalanced datasets is a prominent task in text mining and machine
learning. The number of samples in each class is not uniformly distributed; one class …

Artificial intelligence-based human-centric decision support framework: an application to predictive maintenance in asset management under pandemic environments

J Chen, CP Lim, KH Tan, K Govindan… - Annals of Operations …, 2021‏ - Springer
Pandemic events, particularly the current Covid-19 disease, compel organisations to re-
formulate their day-to-day operations for achieving various business goals such as cost …

Improvement of Bagging performance for classification of imbalanced datasets using evolutionary multi-objective optimization

SE Roshan, S Asadi - Engineering Applications of Artificial Intelligence, 2020‏ - Elsevier
Today, classification of imbalanced datasets, in which the samples belonging to one class is
more than the samples pertaining to other classes, has been paid much attention owing to …

Emotion detection in text: a review

A Seyeditabari, N Tabari, W Zadrozny - arxiv preprint arxiv:1806.00674, 2018‏ - arxiv.org
In recent years, emotion detection in text has become more popular due to its vast potential
applications in marketing, political science, psychology, human-computer interaction …

[PDF][PDF] Multi-granularity chinese word embedding

R Yin, Q Wang, P Li, R Li, B Wang - Proceedings of the 2016 …, 2016‏ - aclanthology.org
This paper considers the problem of learning Chinese word embeddings. In contrast to
English, a Chinese word is usually composed of characters, and most of the characters …

Lexical data augmentation for sentiment analysis

R **ang, E Chersoni, Q Lu, CR Huang… - Journal of the …, 2021‏ - Wiley Online Library
Abstract Machine learning methods, especially deep learning models, have achieved
impressive performance in various natural language processing tasks including sentiment …