mlsanityData to 14 Oct 2026

An Analysis of the Features Considerable for NFT Recommendations

arXiv 2205.00456 ↗First posted 1 May 2022cs.IR cs.CY cs.HCcited by 2

Not on the map. Why?

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.

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

1 of 33 references.

References · 1

  1. 2019Deep Learning Recommendation Model for Personalization and Recommendation Systemscited by 327

Built on by

Cited by year

Citing papers per year: 2023: 1; 2024: 1.

2 papers.

  1. 2023NFTs to MARS: Multi-Attention Recommender System for NFTscited by 0
  2. 2024A Recommender System for NFT Collectibles with Item Featurecited by 0