A lack of power and extensibility in their query languages has seriously limited the generality of DBMSs and hampered their ability to support data mining applications. Thus, ther...
- Filtering the immense amount of data available electronically over the World Wide Web is an important task of search engines in data mining applications. Users when performing se...
Clustering is one of the most important tasks performed in Data Mining applications. This paper presents an e cient SQL implementation of the EM algorithm to perform clustering in...
In this paper we will show that it is possible to combine mobile agent technology with existing non-mobile data mining applications. The motivation for this is the advantage mobil...
In many data mining applications, the data manifold is of lower dimension than the dimension of the input space. In this paper, it is proposed to take advantage of this additional ...
Implementation of data mining applications is a challenging and complicated task, and the applications are often built from scratch. In this paper, a component-based application f...
— 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...
Abstract— Data mining constitutes an important class of scientific and commercial applications. Recent advances in data extraction techniques have created vast data sets, which ...
Biclustering refers to simultaneously capturing correlations present among subsets of attributes (columns) and records (rows). It is widely used in data mining applications includ...
Abstract. We propose a new class of distance measures (metrics) designed for multisets, both of which are a recurrent theme in many data mining applications. One particular instanc...