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On the Approximability of Geometric and Geographic Generalization and the Min-Max Bin Covering Problem
[article]
2009
arXiv
pre-print
We study the problem of abstracting a table of data about individuals so that no selection query can identify fewer than k individuals. We show that it is impossible to achieve arbitrarily good polynomial-time approximations for a number of natural variations of the generalization technique, unless P = NP, even when the table has only a single quasi-identifying attribute that represents a geographic or unordered attribute: Zip-codes: nodes of a planar graph generalized into connected subgraphs
arXiv:0904.3756v3
fatcat:zsrb3a3gtjgmlnaha5uoiumuiq