KRAMER: Interpretable Rarity Meter for Crypto Collectibles
People trade thousands of non-fungible tokens (NFT) daily. The NFT prices are expressed in cryptocurrency, and it is volatile. As the interest in the NFTs changes, their prices vary with time too. Is there an immanent meter to order NFTs by their value? Within a single collection, a vector of featur...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10014994/ |
| Summary: | People trade thousands of non-fungible tokens (NFT) daily. The NFT prices are expressed in cryptocurrency, and it is volatile. As the interest in the NFTs changes, their prices vary with time too. Is there an immanent meter to order NFTs by their value? Within a single collection, a vector of features–traits–characterizes NFT. People construct rarity meters based on the assumed value of the trait vector rarity. But this process lacks formalism. In this paper, we formulate the optimal rarity meter problem and provide a pipeline for optimal rarity meter design. A proposed tournament score function is an essential part of the construction. We demonstrate the approach for the Kanaria NFT collection. |
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| ISSN: | 2169-3536 |