Pattern Masking for Dictionary Matching
Abstract
In the Pattern Masking for Dictionary Matching (PMDM) problem, we are given a dictionary of strings, each of length , a query string of length , and a positive integer , and we are asked to compute a smallest set , so that if , for all , is replaced by a wildcard, then matches at least strings from . The PMDM problem lies at the heart of two important applications featured in large-scale real-world systems: record linkage of databases that contain sensitive information, and query term dropping. In both applications, solving PMDM allows for providing data utility guarantees as opposed to existing approaches. We first show, through a reduction from the well-known -Clique problem, that a decision version of the PMDM problem is NP-complete, even for strings over a binary alphabet. We present a data structure for PMDM that answers queries over in time and requires space , for any parameter . We also approach the problem from a more practical perspective. We show an -time and -space algorithm for PMDM if . We generalize our exact algorithm to mask multiple query strings simultaneously. We complement our results by showing a two-way polynomial-time reduction between PMDM and the Minimum Union problem [Chlamt\'{a}\v{c} et al., SODA 2017]. This gives a polynomial-time -approximation algorithm for PMDM, which is tight under plausible complexity conjectures.
Cite
@article{arxiv.2006.16137,
title = {Pattern Masking for Dictionary Matching},
author = {Panagiotis Charalampopoulos and Huiping Chen and Peter Christen and Grigorios Loukides and Nadia Pisanti and Solon P. Pissis and Jakub Radoszewski},
journal= {arXiv preprint arXiv:2006.16137},
year = {2024}
}
Comments
Published in Algorithmica. Abstract abridged due to arXiv requirements