Digital Token Indexing for Similarity-Based NFT Compliance
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Solution Overview
Problem
Existing technologies fail to effectively manage and prevent the creation of duplicate or similar digital tokens, leading to issues such as copyright violation and digital fraud, particularly in the management of non-fungible tokens (NFTs) due to the lack of robust similarity assessment and management mechanisms.
Innovation Solution
A token management platform (TMP) that assesses the similarity of digital tokens during their lifecycle, using an indexing engine, scoring engine, and smart contract engine to manage and control the creation, alteration, and monitoring of digital tokens, ensuring compliance with existing tokens and smart contracts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing notarized ledger technology and NFT capabilities are used, then digital tokens can be created and stored, but the technology fails to prevent creation of similar or duplicate tokens leading to copyright violation and digital fraud
Solution Approach 1:
The system performs preliminary similarity assessment of digital assets before allowing NFT creation. The indexing engine pre-processes and stores features of existing tokens, enabling the scoring engine to evaluate new tokens against the database before minting occurs, preventing duplicate or infringing tokens from being created in the first place
Solution Approach 2:
The system implements a feedback mechanism where the scoring engine continuously evaluates new digital tokens against the indexed database and provides similarity scores. This feedback loop allows the system to identify potential copyright violations or duplicates and prevent their creation, thereby improving reliability and reducing harmful factors
2Object-generated harmful factors
If similarity assessment mechanisms are implemented to prevent duplicate tokens, then copyright protection improves, but system complexity increases due to additional indexing and scoring engines
Solution Approach 1:
The system divides the complexity into separate modular components: an indexing engine for preprocessing and storing digital asset features, a scoring engine for similarity evaluation, and a smart contract engine for enforcement. This segmentation allows each component to specialize in one function, making the overall system more manageable and maintainable despite the added complexity
Solution Approach 2:
The system introduces an intermediary indexing layer that stores processed features of digital assets. This intermediary structure acts as a buffer between raw digital assets and the similarity assessment process, enabling efficient comparison without directly comparing entire assets, thereby managing complexity through abstraction
3Measurement precision
If comprehensive similarity scoring is performed for all digital tokens, then detection precision of duplicates improves, but processing time and computational resources increase
Solution Approach 1:
The system performs partial similarity assessment by comparing only relevant features extracted by the indexing engine rather than analyzing entire digital assets. The scoring engine focuses computation on key distinguishing features, achieving sufficient detection precision without the excessive time cost of comprehensive full-asset comparison
Data Source
AI summary
Techniques include storing a digital token in at least one non-transitory computer readable memory, wherein the digital token represents underlying data. The techniques further include monitoring changes in the underlying data associated with the digital token over time. The techniques further include determining the underlying data has a deviation from a previous state by comparing current underlying data with previous underlying data. The techniques further include generating a similarity score between the current underlying data and the previous underlying data. The techniques further include updating, based on the deviation, when the similarity score satisfies a satisfaction criteria. The techniques further include triggering at least one programmatic action based on the updating of the digital token.