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

Recommender systems (RS), serving at the forefront of Human-centered AI, are widely
deployed in almost every corner of the web and facilitate the human decision-making …

Past two decades have seen a growing interest in methods for providing privacy preserving
data publishing. Several models, algorithms and system designs have been proposed in the …

Electronic health records (EHRs) are increasingly employed to maintain, store and share
varied types of patient data. The data can also be utilized for various research purposes …

In big data applications, data privacy is one of the most concerned issues because
processing large-scale privacy-sensitive data sets often requires computation resources …

A number of studies on privacy-preserving data mining have been proposed. Most of them
assume that they can separate quasi-identifiers (QIDs) from sensitive attributes. For …

Publishing datasets about individuals that contain both relational and transaction (ie, set-
valued) attributes is essential to support many applications, ranging from healthcare to …

Recommendation system have become one of the most well-liked and accepted way to
solve overload of information or merchandise. By collecting user's personal data for …

As an information carrier, face images contain abundant sensitive information. Due to its
natural weak privacy, direct publishing may divulge privacy. Anonymization Technology and …

Abstract The dissemination of Electronic Health Record (EHR) data, beyond the originating
healthcare institutions, can enable large-scale, low-cost medical studies that have the …