An Analysis of the Features Considerable for NFT Recommendations
This work addresses the challenge of personalized NFT discovery for users on decentralized platforms, but it appears incremental as it builds on existing recommender system methods without introducing a new paradigm.
The research tackled the problem of recommending NFTs to users on marketplaces by exploring the use of NFT traits and multiple recommender systems, resulting in a conclusion that emphasizes the necessity of combining these systems for optimal recommendations.
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.