A Customized Validator Recommender System for PoS Networks Using Similarity-Based Circular Visualization

Abstract

This study analyzes the impact of validator behavior on investor rewards in proof-of-stake (PoS) based blockchain networks and proposes a visualization system to assist investors in selecting appropriate validators. This system enables personalized evaluations through five adjustable indicators tailored to the investor's preferences. By utilizing similarity-based circular visualizations and radar charts, it facilitates the selection and comparison of validators. Additionally, it provides time-series data-based line graphs and raw data-based table views to support detailed comparative analysis among validators. The introduction of such a multifaceted evaluation methodology in staking investments is expected to contribute to the formation of user-customized portfolios and the establishment of optimized investment strategies.