4.7 Article

A dimensionality reduction method for large-scale group decision-making using TF-IDF feature similarity and information loss entropy

Related references

Note: Only part of the references are listed.
Article Computer Science, Information Systems

Personalized Individual Semantics Learning to Support a Large-Scale Linguistic Consensus Process

Yucheng Dong et al.

Summary: In this article, we propose a continual personalized individual semantics learning model to support consensus-reaching in large-scale linguistic group decision making. The model derives personalized numerical scales from linguistic preference data, performs clustering ensemble method for group division and consensus management, and demonstrates its effectiveness through a case study on intelligent route optimization.

ACM TRANSACTIONS ON INTERNET TECHNOLOGY (2023)

Article Multidisciplinary Sciences

A Novel GDMD-PROMETHEE Algorithm Based on the Maximizing Deviation Method and Social Media Data Mining for Large Group Decision Making

Juxiang Wang et al.

Summary: Multi-attribute group decision making is widely used and extensively researched. Public focus on emergencies in social media big data provides valuable reference for decision making. Mining valuable information through online reviews is crucial for decision making.

SYMMETRY-BASEL (2023)

Article Computer Science, Artificial Intelligence

A large scale group decision making system based on sentiment analysis cluster

Jose Ramon Trillo et al.

Summary: This paper introduces a novel method for group decision making, which manages the information generated by a large number of experts using natural language processing. The method includes sentiment analysis to detect the behavior of experts and classify them into groups. Additionally, an optimized consensus analysis process is proposed, simplifying the comparison between experts.

INFORMATION FUSION (2023)

Article Computer Science, Information Systems

Building rankings encompassing multiple criteria to support qualitative decision-making

Marc Serramia et al.

Summary: Decision makers face challenges in comparing and ranking elements based on multiple criteria and personal preferences. This study introduces a new decision-making framework and presents a new method for ranking single elements. It is also proven that the contributions of this study generalize recent results in the field of social choice. The findings are illustrated through a case study on ethical decision-making.

INFORMATION SCIENCES (2023)

Article Management

Multi-criteria Large-Scale Group Decision-Making in Linguistic Contexts: A Perspective of Conflict Analysis and Resolution

Junliang Du et al.

Summary: This paper systematically studies conflict analysis and resolution approach to obtain consensus decision results. Based on Pawlak conflict analysis, it introduces three relations among decision makers, i.e., conflict, neutrality, alliance. It analyzes goal conflicts using linguistic assessment and designs a conflict coordination and feedback mechanism to resolve cognitive conflicts.

GROUP DECISION AND NEGOTIATION (2023)

Article Computer Science, Interdisciplinary Applications

A method for the dynamic collaboration of the public and experts in large-scale group emergency decision-making: Using social media data to evaluate the decision-making quality

Yucheng Zhu et al.

Summary: This article proposes a method for the dynamic collaboration of the public and experts in large-scale group emergency decision-making (LSGEDM) based on social media data, aiming at the complex and changeable environment and the low public participation in emergency decision making. The method includes sentiment analysis of social media data, dynamic updating of attribute weights based on decision-making quality, trust relationship updating between experts based on comprehensive quality and distance, and calculation of expert weights using an improved PageRank algorithm. The effectiveness and superiority of the method are verified through its application to the COVID-19 epidemic in China and a comparative analysis.

COMPUTERS & INDUSTRIAL ENGINEERING (2023)

Article Computer Science, Artificial Intelligence

A global optimization feedback model with PSO for large scale group decision making in hesitant fuzzy linguistic environments

Meng-Ke Zhao et al.

Summary: In an increasingly complex and uncertain decision-making environment, large-scale group decision-making (LSGDM) can offer a more efficient method by allowing a large number of decision-makers (DMs) to participate. This paper proposes a global optimization feedback model with particle swarm optimization (PSO) for LSGDM in hesitant fuzzy linguistic environments. The model includes clustering of DMs, calculation of consensus degrees, and PSO-based generation of recommendation advice. A numerical example related to COVID-19 and comparisons are provided to verify the feasibility and advantages of the proposed method.

EXPERT SYSTEMS WITH APPLICATIONS (2023)

Article Computer Science, Artificial Intelligence

Explainable Crowd Decision Making methodology guided by expert natural language opinions based on Sentiment Analysis with Attention-based Deep Learning and Subgroup Discovery

Cristina Zuheros et al.

Summary: This paper focuses on providing explainability to artificial intelligence systems by using natural language evaluations from social media in crowd decision making. The Explainable Crowd Decision Making based on Subgroup Discovery and Attention Mechanisms (ECDM-SDAM) methodology is proposed, which extracts opinions from social media texts using a deep learning approach and provides explanations through attention mechanisms and subgroup discovery. The methodology is evaluated in a real case study of restaurant choice, showing that it offers understandable explanations for the decision process.

INFORMATION FUSION (2023)

Article Computer Science, Artificial Intelligence

Managing non-cooperative behaviors in large-scale group decision making based on trust relationships and confidence levels of decision makers

Guo-Rui Yang et al.

Summary: In large-scale group decision making events, diverse backgrounds of decision makers (DMs) may result in non-cooperative behaviors, such as bribery, passive participation, and potential conflict. This study proposes a confidence and trust-based consensus reaching process (CT-CRP) to address these behaviors by integrating DMs' evaluations with their personal attributes. CT-CRP introduces three acceptance functions for DMs to determine the likelihood of accepting recommended plans and ensuring optimal modification rate. Experimental results demonstrate the effectiveness and validity of CT-CRP in enhancing consensus among DMs.

INFORMATION FUSION (2023)

Article Computer Science, Information Systems

Large-scale three-way group consensus decision considering individual competition behavior in social networks

Decui Liang et al.

Summary: This paper investigates large-scale group consensus decision in the framework of three-way decision, considering the effects of competitive behaviors in large-scale group social networks. It improves the K-L algorithm and designs identification rules for competition relationship, explores corresponding competitive behaviors, constructs a new optimization consensus model, and verifies its effectiveness in an example of product promotion.

INFORMATION SCIENCES (2023)

Article Engineering, Chemical

A Study of Text Vectorization Method Combining Topic Model and Transfer Learning

Xi Yang et al.

Summary: With the development of Internet cloud technology, the scale of data is expanding rapidly, causing difficulties for traditional processing methods in extracting information from big data. Therefore, this paper proposes a text vectorization method combining topic modeling and transfer learning, which extracts keywords and generates vectors to calculate the similarity between texts. Experimental results show that this method has advantages in calculating the similarity between texts with the same topic.

PROCESSES (2022)

Article Automation & Control Systems

Consensus Model Handling Minority Opinions and Noncooperative Behaviors in Large-Scale Group Decision-Making Under Double Hierarchy Linguistic Preference Relations

Xunjie Gou et al.

Summary: This article explores the management of minority opinions and noncooperative behaviors in large-scale group decision-making, proposing a consensus model and developing corresponding basic tools. Through a practical case study, it demonstrates the feasibility and effectiveness of the consensus model.

IEEE TRANSACTIONS ON CYBERNETICS (2021)

Article Computer Science, Artificial Intelligence

A hesitant fuzzy linguistic bi-objective clustering method for large-scale group decision-making

Yuanhang Zheng et al.

Summary: This paper proposes a hesitant fuzzy linguistic bi-objective clustering method considering consensus and information entropy for tackling large-scale group decision-making problems, which shows good performance and strong robustness.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

Article Management

Adaptive consensus reaching process with hybrid strategies for large-scale group decision making

Ming Tang et al.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2020)

Article Computer Science, Information Systems

Interval multiplicative pairwise comparison matrix: Consistency, indeterminacy and normality

Ting Kuo

INFORMATION SCIENCES (2020)

Article Automation & Control Systems

A Novel Probabilistic Linguistic Approach for Large-Scale Group Decision Making with Incomplete Weight Information

Xiaolu Zhang

INTERNATIONAL JOURNAL OF FUZZY SYSTEMS (2018)