Multi-Party Privacy Preserving Record Linkage in Dynamic Metric Space
| dc.contributor.author | Sehili, Ziad | |
| dc.contributor.author | Rohde, Florens | |
| dc.contributor.author | Franke, Martin | |
| dc.contributor.author | Rahm, Erhard | |
| dc.contributor.editor | Kai-Uwe Sattler | |
| dc.contributor.editor | Melanie Herschel | |
| dc.contributor.editor | Wolfgang Lehner | |
| dc.date.accessioned | 2021-03-16T07:57:09Z | |
| dc.date.available | 2021-03-16T07:57:09Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | We propose and evaluate several approaches for multi-party privacy-preserving record linkage (MP-PPRL) for multiple data sources. To reduce the number of comparisons for scalability we propose a new pivot-based metric space approach that dynamically adapts the selection of pivots for additional sources and growing data volume. We investigate so-called early and late clustering schemes that either cluster matching records per additional source or holistically for all sources. A comprehensive evaluation for different datasets confirms the high effectiveness and efficiency of the proposed methods. | en |
| dc.identifier.doi | 10.18420/btw2021-13 | |
| dc.identifier.isbn | 978-3-88579-705-0 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/35796 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik, Bonn | |
| dc.relation.ispartof | BTW 2021 | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-311 | |
| dc.subject | Privacy Preserving Record Linkage | |
| dc.subject | Bloom filter | |
| dc.subject | metric space | |
| dc.subject | triangle inequality | |
| dc.subject | Clustering | |
| dc.title | Multi-Party Privacy Preserving Record Linkage in Dynamic Metric Space | en |
| gi.citation.endPage | 278 | |
| gi.citation.startPage | 257 | |
| gi.conference.date | 13.-17. September 2021 | |
| gi.conference.location | Dresden | |
| gi.conference.sessiontitle | Data Integration, Semantic Data Management, Streaming |
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