# An Analysis of the Features Considerable for NFT Recommendations

arXiv: https://arxiv.org/abs/2205.00456 · HTML: https://mlsanity.com/paper/2205.00456/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 33 references that are in the map.
- First posted on arXiv 1 May 2022.

## Builds on (most cited first, 1 of 1)

- [Deep Learning Recommendation Model for Personalization and Recommendation Systems](https://mlsanity.com/paper/1906.00091/) (2019)

## Built on by (most cited first, 2 of 2)

- [NFTs to MARS: Multi-Attention Recommender System for NFTs](https://mlsanity.com/paper/2306.10053/) (2023)
- [A Recommender System for NFT Collectibles with Item Feature](https://mlsanity.com/paper/2403.18305/) (2024)

## Abstract (arXiv)

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.