Large and complex graphs representing relationships among sets of entities are an increasingly common focus of interest in data analysis--examples include social networks, Web gra...
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...
We developed Relational Data Mining approach which allows to overcome essential limitations of the Data Mining and Knowledge Discovery techniques. In the paper the approach was im...
I. V. Khomicheva, Eugenii E. Vityaev, Elena A. Ana...
How can we automatically spot all outstanding observations in a data set? This question arises in a large variety of applications, e.g. in economy, biology and medicine. Existing ...
Biclustering refers to simultaneously capturing correlations present among subsets of attributes (columns) and records (rows). It is widely used in data mining applications includ...