The focus of this paper is to develop algorithms and a framework for modeling transactional data stored in relational database into graphs for mining. Most of the real-world trans...
Modern geographic databases can contain a large volume of data that need to be distributed to subscribed customers. The data can be modeled as a cube, where typical dimensions inc...
There is a huge wealth of sequence data available, for example, customer purchase histories, program execution traces, DNA, and protein sequences. Analyzing this wealth of data to ...
Randomization is an economical and efficient approach for privacy preserving data mining (PPDM). In order to guarantee the performance of data mining and the protection of individ...
Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...