Traditional data mining applications consider the problem of mining a single relation between two attributes. For example, in a scientific bibliography database, authors are rela...
Foto N. Afrati, Gautam Das, Aristides Gionis, Heik...
— Data mining is the process of automatically finding implicit, previously unknown, and potentially useful information from large volumes of data. Recent advances in data extrac...
In this paper, we discuss a problem of finding risk patterns in medical data. We define risk patterns by a statistical metric, relative risk, which has been widely used in epidemi...
Jiuyong Li, Ada Wai-Chee Fu, Hongxing He, Jie Chen...
Data mining applications analyze large collections of set data and high dimensional categorical data. Search on these data types is not restricted to the classic problems of minin...
In this paper we: introduce EMADS, the Extendible Multi-Agent Data mining System, to support the dynamic creation of communities of data mining agents; explore the capabilities of ...