A systematic review on affective computing: Emotion models, databases, and recent advances
Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
A comprehensive survey on word representation models: From classical to state-of-the-art word representation language models
Word representation has always been an important research area in the history of natural
language processing (NLP). Understanding such complex text data is imperative, given that …
language processing (NLP). Understanding such complex text data is imperative, given that …
Improving multimodal fusion with hierarchical mutual information maximization for multimodal sentiment analysis
In multimodal sentiment analysis (MSA), the performance of a model highly depends on the
quality of synthesized embeddings. These embeddings are generated from the upstream …
quality of synthesized embeddings. These embeddings are generated from the upstream …
Decoupled multimodal distilling for emotion recognition
Human multimodal emotion recognition (MER) aims to perceive human emotions via
language, visual and acoustic modalities. Despite the impressive performance of previous …
language, visual and acoustic modalities. Despite the impressive performance of previous …
Sentiment analysis of Twitter data during critical events through Bayesian networks classifiers
Sentiment analysis through machine learning using Twitter data has become a popular topic
in recent years. Here we address the problem of sentiment analysis during critical events …
in recent years. Here we address the problem of sentiment analysis during critical events …
[HTML][HTML] Comparing automated text classification methods
J Hartmann, J Huppertz, C Schamp… - International Journal of …, 2019 - Elsevier
Online social media drive the growth of unstructured text data. Many marketing applications
require structuring this data at scales non-accessible to human coding, eg, to detect …
require structuring this data at scales non-accessible to human coding, eg, to detect …
A review of affective computing: From unimodal analysis to multimodal fusion
Affective computing is an emerging interdisciplinary research field bringing together
researchers and practitioners from various fields, ranging from artificial intelligence, natural …
researchers and practitioners from various fields, ranging from artificial intelligence, natural …
A survey of multimodal sentiment analysis
Sentiment analysis aims to automatically uncover the underlying attitude that we hold
towards an entity. The aggregation of these sentiment over a population represents opinion …
towards an entity. The aggregation of these sentiment over a population represents opinion …
[图书][B] Machine learning for text: An introduction
CC Aggarwal, CC Aggarwal - 2018 - Springer
The extraction of useful insights from text with various types of statistical algorithms is
referred to as text mining, text analytics, or machine learning from text. The choice of …
referred to as text mining, text analytics, or machine learning from text. The choice of …
[HTML][HTML] Enhancing deep learning sentiment analysis with ensemble techniques in social applications
O Araque, I Corcuera-Platas, JF Sánchez-Rada… - Expert Systems with …, 2017 - Elsevier
Deep learning techniques for Sentiment Analysis have become very popular. They provide
automatic feature extraction and both richer representation capabilities and better …
automatic feature extraction and both richer representation capabilities and better …