Value-specific Weighting for Record-level Encodings in Privacy-Preserving Record Linkage
| dc.contributor.author | Rohde, Florens | |
| dc.contributor.author | Franke, Martin | |
| dc.contributor.author | Christen, Victor | |
| dc.contributor.author | Rahm, Erhard | |
| dc.contributor.editor | König-Ries, Birgitta | |
| dc.contributor.editor | Scherzinger, Stefanie | |
| dc.contributor.editor | Lehner, Wolfgang | |
| dc.contributor.editor | Vossen, Gottfried | |
| dc.date.accessioned | 2023-02-23T13:59:50Z | |
| dc.date.available | 2023-02-23T13:59:50Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Privacy-preserving record linkage (PPRL) determines records representing the same entitywhile guaranteeing the privacy of individuals. A common approach is to encode plaintext data ofrecords into Bloom filters that enable efficient calculation of similarities. A crucial step of PPRL isthe classification of Bloom filter pairs as match or non-match based on computed similarities. In thecontext of record linkage, several weighting schemes and classification methods are available. Themajority of weighting methods determine and adapt weights by applying the Fellegi&Sunter modelfor each attribute. In the PPRL domain, the attributes of a record are encoded in a joint record-levelBloom filter to impede cryptanalysis attacks so that the application of existing attribute-wise weightingapproaches is not feasible. We study methods that use attribute-specific weights in record-levelencodings and integrate weight adaptation approaches based on individual value frequencies. Theexperiments on real-world datasets show that frequency-dependent weighting schemes improve thelinkage quality as well as the robustness with regard to the threshold selection. | en |
| dc.identifier.doi | 10.18420/BTW2023-21 | |
| dc.identifier.isbn | 978-3-88579-725-8 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/40326 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | BTW 2023 | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-331 | |
| dc.subject | Privacy-preserving record linkage | |
| dc.subject | Bloom filter | |
| dc.subject | Weighting | |
| dc.subject | Value-specific | |
| dc.title | Value-specific Weighting for Record-level Encodings in Privacy-Preserving Record Linkage | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 460 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 439 | |
| gi.conference.date | 06.-10. März 2023 | |
| gi.conference.location | Dresden, Germany |
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