Hierarchical clustering methods are widely used in various scientific domains such as molecular biology, medicine, economy, etc. Despite the maturity of the research field of hie...
The burgeoning amount of textual data in distributed sources combined with the obstacles involved in creating and maintaining central repositories motivates the need for effective ...
Shenzhi Li, Christopher D. Janneck, Aditya P. Bela...
One of the inherent problems in pattern recognition is the undersampled data problem, also known as the curse of dimensionality reduction. In this paper a new algorithm called pai...
This paper presents an overview of the motivation for, and the use of time-series data mining in, a Geospatial Decision Support System (GDSS). Our approach is based on a combinati...
Dan Li, Sherri K. Harms, Steve Goddard, William J....
While the emerging field of privacy preserving data mining (PPDM) will enable many new data mining applications, it suffers from several practical difficulties. PPDM algorithms are...
Jimmy Secretan, Anna Koufakou, Michael Georgiopoul...