Bloom filter (BF) has been widely used to support membership query, ie, to judge whether a
given element x is a member of a given set S or not. Recent years have seen a flourish …

Abstract The growth of Big Data, especially personal data dispersed in multiple data
sources, presents enormous opportunities and insights for businesses to explore and …

Sensitive personal data are created in many application domains, and there is now an
increasing demand to share, integrate, and link such data within and across organisations in …

Record linkage is the challenging task of deciding which records, coming from disparate
data sources, refer to the same entity. Established back in 1946 by Halbert L. Dunn, the area …

Private record linkage (PRL) is the problem of identifying pairs of records that are similar as
per an input matching rule from databases held by two parties that do not trust one another …

Recent advances in telecommunications and database systems have allowed the scientific
community to efficiently mine vast amounts of information worldwide and to extract new …

Federated learning is a learning paradigm to enable collaborative learning across different
parties without revealing raw data. Notably, vertical federated learning (VFL), where parties …

Deep learning-based linkage of records across different databases is becoming increasingly
useful in data integration and mining applications to discover new insights from multiple data …

Bloom filter encoding has widely been used as an efficient masking technique for privacy-
preserving matching functions. The existing matching techniques, however, are limited to …

Entity Resolution (ER) is a fundamental problem in data preparation. Standard deep ER
methods have achieved state-of-the-art effectiveness, assuming that relations from different …