: se the concept of visualizing general abstract data by intermediate projection into the hyperbolic space. Its favorable properties were reported earlier and led to the "hype...
Privacy considerations often constrain data mining projects. This paper addresses the problem of association rule mining where transactions are distributed across sources. Each si...
Rule mining is an important data mining task that has been applied to numerous real-world applications. Often a rule mining system generates a large number of rules and only a sma...
The problem of analyzing microarray data became one of important topics in bioinformatics over the past several years, and different data mining techniques have been proposed for ...
The task of object identification occurs when integrating information from multiple websites. The same data objects can exist in inconsistent text formats across sites, making it ...
The goal of clustering is to identify distinct groups in a dataset. Compared to non-parametric clustering methods like complete linkage, hierarchical model-based clustering has th...
Many techniques for association rule mining and feature selection require a suitable metric to capture the dependencies among variables in a data set. For example, metrics such as...
The banking industry regularly mounts campaigns to improve customer value by offering new products to existing customers. In recent years this approach has gained significant mome...
In the last several years, large OLAP databases have become common in a variety of applications such as corporate data warehouses and scientific computing. To support interactive ...