An Analysis of the Features Considerable for NFT Recommendations

TL;DR

This paper investigates NFT recommendation methods, emphasizing the importance of combining multiple recommender systems and utilizing NFT traits to enhance user experience in decentralized marketplaces.

Contribution

It introduces a comprehensive analysis of NFT features for recommendations and advocates for hybrid approaches to improve recommendation quality.

Findings

NFT traits are crucial for effective recommendations

Multiple recommender systems outperform single methods

Hybrid approaches enhance user satisfaction in NFT marketplaces

Abstract

This research explores the methods that NFTs can be recommended to people who interact with NFT-marketplaces to explore NFTs of preference and similarity to what they have been searching for. While exploring past methods that can be adopted for recommendations, the use of NFT traits for recommendations has been explored. The outcome of the research highlights the necessity of using multiple Recommender Systems to present the user with the best possible NFTs when interacting with decentralized systems.