Probabilistic relational data mining

Abstract

Probabilistic Relational Data Mining (PRDM) refers to the use of Knowledge discovery in database (KDD) methods of learning probabilistic statistical models from relational data that has information about several types of objects. This is usually the case when the database has more than one table. PRDM provides techniques for discovering descriptive models, including relationships, correlations and causal dependencies, embedded in a set of objects as well as their component attributes. In essence, it is a marriage of probabilistic modeling, multi-relational database modeling, and object oriented modeling. The three modeling processes are integrated together into a data mining system to fulfill the overall modeling task, in which, intuitively speaking, database modeling plays a role of input, probabilistic modeling is like an output, and objectoriented modeling provides necessary background information.

Cryptography and Security in Computing

“…Privacy concerns may also arise beyond data content and may focus on context information such as the location of a sensor initiating data communication. Effective countermeasure against the disclosure of both data and context-oriented private information is an indispensable prerequisite for deployment of WSNs in real-world applications (Sen, 2010a;Bandyopadhyay & Sen, 2011).…”