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[HTML][HTML] A review of ensemble learning and data augmentation models for class imbalanced problems: Combination, implementation and evaluation
Class imbalance (CI) in classification problems arises when the number of observations
belonging to one class is lower than the other. Ensemble learning combines multiple models …
belonging to one class is lower than the other. Ensemble learning combines multiple models …
Corporate financial distress prediction using the risk-related information content of annual reports
This study presents a financial distress prediction model focusing on the linguistic analysis
of risk-related sections of corporate annual reports. Here, we introduce a novel methodology …
of risk-related sections of corporate annual reports. Here, we introduce a novel methodology …
[HTML][HTML] A systematic literature review of modalities, trends, and limitations in emotion recognition, affective computing, and sentiment analysis
This systematic literature review delves into the extensive landscape of emotion recognition,
sentiment analysis, and affective computing, analyzing 609 articles. Exploring the intricate …
sentiment analysis, and affective computing, analyzing 609 articles. Exploring the intricate …
An improved MSER using grid search based PCA and ensemble voting technique
Recognizing speech emotions is indeed a crucial aspect of human–computer interaction.
However, develo** a model that can accurately process multiple languages is one of the …
However, develo** a model that can accurately process multiple languages is one of the …
[HTML][HTML] Temporal convolutional networks and BERT-based multi-label emotion analysis for financial forecasting
The use of deep learning in conjunction with models that extract emotion-related information
from texts to predict financial time series is based on the assumption that what is said about …
from texts to predict financial time series is based on the assumption that what is said about …
Credit rating prediction using a fuzzy MCDM approach with criteria interactions and TOPSIS sorting
Multi-criteria decision making (MCDM) provides effective methods for dealing with the
challenge of sorting credit ratings. This paper presents a novel data-driven MCDM sorting …
challenge of sorting credit ratings. This paper presents a novel data-driven MCDM sorting …
[HTML][HTML] An online review data-driven fuzzy large-scale group decision-making method based on dual fine-tuning
Large-scale group decision-making (LSGDM) involves aggregating the opinions of
participating decision-makers into collective opinions and selecting optimal solutions …
participating decision-makers into collective opinions and selecting optimal solutions …
[HTML][HTML] Fine-Tuning Retrieval-Augmented Generation with an Auto-Regressive Language Model for Sentiment Analysis in Financial Reviews
Sentiment analysis is a well-known task that has been used to analyse customer feedback
reviews and media headlines to detect the sentimental personality or polarisation of a given …
reviews and media headlines to detect the sentimental personality or polarisation of a given …
XEmoAccent: Embracing Diversity in Cross-Accent Emotion Recognition using Deep Learning
Speech is a powerful means to expressing thoughts, emotions, and perspectives. However,
accurately determining the emotions conveyed through speech remains a challenging task …
accurately determining the emotions conveyed through speech remains a challenging task …
The Effect of Analysts' Reports on Stock Liquidity: The Interaction of Ratings and Qualitative Indicators
G Wang, Y Wang, Y Dong, X Shen - Journal of Behavioral Finance, 2024 - Taylor & Francis
We utilized a Python program to collect analysts' reports on the constituents of the CSI 300
(China Securities Index). From these reports, we extracted analyst ratings, readability, and …
(China Securities Index). From these reports, we extracted analyst ratings, readability, and …