Abstract
Self-Sovereign Identity (SSI) is a privacy-preserving identity paradigm where users own and manage their digital identities. SSI is also referred to as blockchain identity, as it is commonly implemented using distributed ledger technologies. In this work, we describe the problem of schema matching on blockchain-based SSI implementations, systematically review the literature for tools that attack this problem, introduce a novel solution, and empirically compare it with the works reported from our literature review. Our solution uses pre-trained word vectors to find semantic similarities between user queries and schemas on the blockchain. Experimental evaluation shows that it outperforms existing solutions regarding queries that approach natural language.
This study was supported by the Federal Institute of Education, Science and Technology of Rio Grande do Sul (IFRS).
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Notes
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The terms metadata and schemas are used interchangeably in this paper.
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Schardong, F., Custódio, R., Pioli, L., Meyer, J. (2022). Matching Metadata on Blockchain for Self-Sovereign Identity. In: Marrella, A., Weber, B. (eds) Business Process Management Workshops. BPM 2021. Lecture Notes in Business Information Processing, vol 436. Springer, Cham. https://doi.org/10.1007/978-3-030-94343-1_32
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