Software is a ubiquitous component of our daily life. We often depend on the correct working of software systems. Due to the difficulty and complexity of software systems, bugs an...
David Lo, Hong Cheng, Jiawei Han, Siau-Cheng Khoo,...
The primary aim of most data mining algorithms is to facilitate the discovery of concise and interpretable information from large amounts of data. However, many of the current for...
—An efficient algorithm for mining important association rule from multi-relational database using distributed mining ideas. Most existing data mining approaches look for rules i...
We study the interaction between global and local techniques in data mining. Specifically, we study the collections of frequent sets in clusters produced by a probabilistic clust...
In this paper, we propose a post randomization technique to learn a Bayesian network (BN) from distributed heterogeneous data, in a privacy sensitive fashion. In this case, two or ...