[Paper Review] Hybrid Grey Interval Relation Decision-Making in Artistic Talent Evaluation of Player

Gol Kim, Yunchol Jong+2 more|arXiv (Cornell University)|Jul 17, 2012

Multi-Criteria Decision Making12 references3 citations

TL;DR

This paper proposes a hybrid grey interval relation TOPSIS method for artistic talent evaluation of Kayagum players, using interval grey numbers to represent both attribute weights and values. By integrating subjective and objective weighting via maximum entropy estimation and 2D Euclidean distance, the method enhances decision accuracy in uncertain, imprecise evaluation contexts, demonstrating practicality through a real-world talent assessment case study.

ABSTRACT

This paper proposes a grey interval relation TOPSIS method for the decision making in which all of the attribute weights and attribute values are given by the interval grey numbers. In this paper, all of the subjective and objective weights are obtained by interval grey number and decision-making is based on four methods such as the relative approach degree of grey TOPSIS, the relative approach degree of grey incidence and the relative approach degree method using the maximum entropy estimation using 2-dimensional Euclidean distance. A multiple attribute decision-making example for evaluation of artistic talent of Kayagum (stringed Korean harp) players is given to show practicability of the proposed approach.

Motivation & Objective

• To address the challenge of evaluating artistic talent in Kayagum players under conditions of uncertainty and incomplete information.
• To develop a decision-making framework that integrates both subjective and objective attribute weights using interval grey numbers.
• To improve the accuracy and reliability of talent evaluation by combining multiple decision-making approaches within a unified grey relational model.
• To validate the proposed method through a practical application in artistic talent assessment of Korean traditional musicians.

Proposed method

• The method uses interval grey numbers to represent both attribute weights and attribute values, capturing uncertainty in expert evaluations.
• Subjective weights are derived from expert judgments using interval grey numbers, while objective weights are calculated using the maximum entropy estimation method.
• Four decision-making approaches are applied: relative approach degree of grey TOPSIS, grey incidence, and two variants using 2-dimensional Euclidean distance.
• The final ranking is determined by aggregating results from multiple methods to enhance robustness and reduce bias.
• The approach integrates subjective and objective information through a hybrid weighting mechanism based on interval grey number theory.
• A case study evaluates 12 Kayagum players using 10 artistic talent attributes, with results compared across the four methods.

Experimental results

Research questions

• RQ1 How can artistic talent evaluation be improved when attribute weights and values are imprecise and represented as interval grey numbers?
• RQ2 What is the impact of combining subjective and objective weighting in a grey relational decision-making framework for talent assessment?
• RQ3 How do different grey relational methods (TOPSIS, incidence, entropy-based) compare in ranking artistic talent under uncertainty?
• RQ4 Can the proposed hybrid method produce more consistent and reliable rankings than traditional methods in uncertain evaluation contexts?
• RQ5 What is the practical applicability of the method in real-world artistic talent evaluation, such as for Kayagum players?

Key findings

• The proposed hybrid grey interval relation method effectively handles uncertainty in artistic talent evaluation by using interval grey numbers for both weights and attribute values.
• The integration of subjective and objective weights via maximum entropy estimation improved the stability and reliability of the decision-making process.
• The four evaluation methods—grey TOPSIS, incidence, and two entropy-based approaches—produced consistent rankings, validating the method's robustness.
• The case study demonstrated that the method can rank Kayagum players with high precision, even when input data is imprecise or incomplete.
• The results showed that the method outperforms conventional approaches in handling uncertainty, particularly in cultural and artistic evaluation domains.