A Recommendation Mechanism for a Non-Fungible Token Trading Platform

Abstract

Technology has evolved at an increasing pace over the decades, blockchain is used in many fields, and Non-Fungible Token (NFT) is one of its applications. With NFT, all digital assets can be freely traded because NFT establishes a unique token for each asset. From the transaction statistics, it can be found that the transaction volume in the past six months has increased explosively, and the projects uploaded to the NFT trading platform have also increased; but it also means customers need to spend more time finding what they want. Active recommendation systems can be used to solve this problem to reduce search cost. This study proposes a recommendation system for NFT tokens, compares the similarity between items, and analyzes buyers' collection data to prove that the recommendation theory proposed in this study is valid.