Data mining on large relational databases has gained popularity and its significance is well recognized. However, the performance of SQL based data mining is known to fall behind ...
The concern about national security has increased significantly since the 9/11 attacks. However, information overload hinders the effective analysis of criminal and terrorist activ...
Hsinchun Chen, Wingyan Chung, Yi Qin, Michael Chau...
In this paperwedescribe the prototypeof a yellowpageservice for customersin a distributed cyber-shoppingmall. This application combines distributed data miningwith agent technolog...
Yugyung Lee, James Geller, Eun Kyo Park, Changgyu ...
Data mining focuses on the development of methods and algorithms for such tasks as classification, clustering, rule induction, and discovery of associations. In the database fiel...
- The KDD (Knowledge Discovery in Databases) paradigm is a step by step process for finding interesting patterns in large amounts of data. Data mining is one step in the process. T...
Electronic surveys are an important resource in data mining. However, how to protect respondents' data privacy during the survey is a challenge to the security and privacy co...
Accurate demand forecasting remains difficult and challenging in today's competitive and dynamic business environment, but even a little improvement in demand prediction may ...
This paper describes the application of online analytical processing (OLAP) in the field of data mining. We discuss knowledge discovery in enterprise databases as well as data war...