Hiding information by cell suppression
Joining relational data can jeopardize patient confidentiality if disseminated data for research can be joined with publicly available data containing, for example, explicit identifiers. Ambiguity in data hinders the construction of primary keys that are of importance when joining data tables. We de...
| Veröffentlicht in: | Proceedings. AMIA Symposium. - 1998. - (2001) vom: 11., Seite 726-30 |
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| Weitere Verfasser: | , |
| Format: | Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2001
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| Zugriff auf das übergeordnete Werk: | Proceedings. AMIA Symposium |
| Schlagworte: | Journal Article Research Support, U.S. Gov't, P.H.S. |
| Zusammenfassung: | Joining relational data can jeopardize patient confidentiality if disseminated data for research can be joined with publicly available data containing, for example, explicit identifiers. Ambiguity in data hinders the construction of primary keys that are of importance when joining data tables. We define two values to be indiscernible if they are the same or at least one of them is a special value. Two rows in a data table are indiscernible if their corresponding entries are indiscernible. We further define a table to be k-ambiguous if each row is indiscernible from at least k rows in the same table. We present two simple heuristics to make a table k-ambiguous by cell suppression, and compare them on example data |
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| Beschreibung: | Date Completed 24.05.2002 Date Revised 13.11.2018 published: Print Citation Status MEDLINE |
| ISSN: | 1531-605X |