A generic and extendible Multi-Agent Data Mining (MADM) framework, EMADS (the Extendible Multi-Agent Data mining System) is described. The central feature of the framework is that ...
The education domain offers a fertile ground for many interesting and challenging data mining applications. These applications can help both educators and students, and improve th...
Yiming Ma, Bing Liu, Ching Kian Wong, Philip S. Yu...
As the size of available datasets in various domains is growing rapidly, there is an increasing need for scaling data mining implementations. Coupled with the current trends in co...
This paper proposes a novel multiclass classification method and exhibits its advantage in the domain of text categorization with a large label space and, most importantly, when ...
We describe a open-domain information extraction method for extracting concept-instance pairs from an HTML corpus. Most earlier approaches to this problem rely on combining cluste...
Bhavana Bharat Dalvi, William W. Cohen, Jamie Call...