[HTML][HTML] A recent overview of the state-of-the-art elements of text classification

MM Mirończuk, J Protasiewicz - Expert Systems with Applications, 2018 - Elsevier
The aim of this study is to provide an overview the state-of-the-art elements of text
classification. For this purpose, we first select and investigate the primary and recent studies …

ELECTRE: A comprehensive literature review on methodologies and applications

K Govindan, MB Jepsen - European Journal of Operational Research, 2016 - Elsevier
Multi-criteria decision analysis (MCDA) is a valuable resource within operations research
and management science. Various MCDA methods have been developed over the years …

[HTML][HTML] Evaluation of feature selection methods for text classification with small datasets using multiple criteria decision-making methods

G Kou, P Yang, Y Peng, F Xiao, Y Chen… - Applied Soft Computing, 2020 - Elsevier
The evaluation of feature selection methods for text classification with small sample datasets
must consider classification performance, stability, and efficiency. It is, thus, a multiple …

[HTML][HTML] Forecasting and trading cryptocurrencies with machine learning under changing market conditions

H Sebastião, P Godinho - Financial Innovation, 2021 - Springer
This study examines the predictability of three major cryptocurrencies—bitcoin, ethereum,
and litecoin—and the profitability of trading strategies devised upon machine learning …

[HTML][HTML] Soft consensus cost models for group decision making and economic interpretations

H Zhang, G Kou, Y Peng - European Journal of Operational Research, 2019 - Elsevier
In a group decision-making (GDM) process, experts reach a consensus after discussion and
persuasion, which requires a moderator to spend time and resource to persuade experts to …

Machine learning methods for systemic risk analysis in financial sectors.

G Kou, X Chao, Y Peng, FE Alsaadi, E Herrera Viedma - 2019 - digibug.ugr.es
Financial systemic risk is an important issue in economics and financial systems. Trying to
detect and respond to systemic risk with growing amounts of data produced in financial …

Development of TOPSIS method to solve complicated decision-making problems—An overview on developments from 2000 to 2015

EK Zavadskas, A Mardani, Z Turskis… - … journal of information …, 2016 - World Scientific
In recent years several previous scholars made attempts to develop, extend, propose and
apply Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for solving …

[HTML][HTML] Comprehensive review of text-mining applications in finance

A Gupta, V Dengre, HA Kheruwala, M Shah - Financial Innovation, 2020 - Springer
Text-mining technologies have substantially affected financial industries. As the data in
every sector of finance have grown immensely, text mining has emerged as an important …

Evaluating solutions to overcome humanitarian supply chain management barriers: A hybrid fuzzy SWARA–Fuzzy WASPAS approach

S Agarwal, R Kant, R Shankar - International Journal of Disaster Risk …, 2020 - Elsevier
This study intends to explore humanitarian supply chain management barriers (HSCMBs)
and evaluate solutions for overcoming these barriers to improve humanitarian supply chain …

State of art surveys of overviews on MCDM/MADM methods

EK Zavadskas, Z Turskis, S Kildienė - Technological and economic …, 2014 - Taylor & Francis
Decision-making is primarily a process that involves different actors: people, groups of
people, institutions and the state. As a discipline, multi-criteria decision-making has a …