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[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 …
in texts. Various Deep Learning (DL) methods have developed rapidly, and they have …
[HTML][HTML] Learning from imbalanced data: open challenges and future directions
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 …
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
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 …
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
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 …
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
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 …
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
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 …
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
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 …
more than the samples pertaining to other classes, has been paid much attention owing to …
Emotion detection in text: a review
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 …
applications in marketing, political science, psychology, human-computer interaction …
[PDF][PDF] Multi-granularity chinese word embedding
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 …
English, a Chinese word is usually composed of characters, and most of the characters …
Lexical data augmentation for sentiment analysis
Abstract Machine learning methods, especially deep learning models, have achieved
impressive performance in various natural language processing tasks including sentiment …
impressive performance in various natural language processing tasks including sentiment …