Abstract. One of the most interesting challenges in Knowledge Discovery in Databases (KDD) eld is giving support to users in the composition of tools for forming a valid and useful...
Complexity of post-genomic data and multiplicity of mining strategies are two limits to Knowledge Discovery in Databases (KDD) in life sciences. Because they provide a semantic fr...
In recent years, the KDD process has been advocated to be an iterative and interactive process. It is seldom the case that a user is able to answer immediately with a single query...
Arianna Gallo, Roberto Esposito, Rosa Meo, Marco B...
In the last years there has been a huge growth and consolidation of the Data Mining field. Some efforts are being done that seek the establishment of standards in the area. Includ...
Data mining applications are typically used in the decision making process. The Knowledge Discovery Process (KDD process for short) is a typical iterative process, in which not on...
KDD (Knowledge Discovery in Databases) processhas become a new and important research area. Within the framework of KDD process and the GLS (Global Learning Scheme) system recentl...
Ning Zhong, Chunnian Liu, Yoshitsugu Kakemoto, Set...
The KDD process aims at the discovery and extraction of “useful” knowledge (such as interesting patterns, classification, rules etc) from large data repositories. A widely rec...
Visualization techniques provide an outstanding role in KDD process for data analysis and mining. However, one image does not always convey successfully the inherent information fr...