This study investigates existing input privacy-preserving data mining (PPDM) methods and
privacy-preserving data stream mining methods (PPDSM), including their strengths and …

A database that contains personal information and is collected by crowdsensing can be
used for various purposes. Therefore, database holders may want to share their databases …

Nearly most of the organizations store massive amounts of data in large databases for
research, statistics, and mining purposes. In most cases, much of the accumulated data …

Nowadays, researchers have shown significant interest in geographic location-based spatial
data analysis due to its wide range of application scenarios. However, the accuracy of the …

The key problem of using differential privacy is controlling sensitivity. Almost all papers focus
on processing sensitivity, but the efficiency of the algorithm is also very important. Therefore …

This study investigates existing input privacy-preserving data mining (PPDM) methods and
privacy-preserving data stream mining methods (PPDSM), including their strengths and …

With the rapid development of mobile Internet, trajectory data has become an indispensable
data type in the era of big data due to its potential information. Since trajectory data of real …

Data streams differ from static datasets due to numerous characteristics such as being
incremental, high speed, high volume, subject to concept drift, and dynamically adapting …

In this information age, large amount of data is available online. These data are used by
both internal and external sources for analysis and research purposes. The collected data is …

The goal of the Semantic Web is to publish datasets, mainly as RDF, describing and
combining resources on the Web for an open access. The datasets are usually treated and …