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

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 …

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 …

This paper presents a set of new run-time tests for speculative parallelization of loops that
defy parallelization based on static analysis alone. It presents a novel method for …

With the rapid development of IoT, data from various devices is increasing exponentially. To
better apply and analyze IoT data, it is necessary to integrate them from different parties …

Abstract Privacy-Preserving Record Linkage (PPRL) supports the integration of sensitive
information from multiple datasets, in particular the privacy-preserving matching of records …

The integration, mining, and analysis of person-specific data can provide enormous
opportunities for organizations, governments, and researchers to leverage today's massive …

Record linkage algorithms match and link records from different databases that refer to the
same real-world entity based on direct and/or quasi-identifiers, such as name, address, age …

In many application domains organizations require information from multiple sources to be
integrated. Due to privacy and confidentiality concerns often these organizations are not …

The problem of identifying duplicated entities in a dataset has gained increasing importance
during the last decades. Due to the large size of the datasets, this problem can be very costly …