The partitional clustering concept started with K-means algorithm which was published in
1957. Since then many classical partitional clustering algorithms have been reported based …

Ant-based clustering is a biologically inspired data clustering technique. Clustering task
aims at the unsupervised classification of patterns in different groups. Clustering problem …

We develop a model of neural networks to study the bankruptcy of US banks, taking into
account the specific features of the recent financial crisis. We combine multilayer …

We contend that corruption must be detected as soon as possible so that corrective and
preventive measures may be taken. Thus, we develop an early warning system based on a …

Clustering is a popular data analysis and data mining technique. It is the unsupervised
classification of patterns into groups. Many algorithms for large data sets have been …

Ant-tree is a clustering algorithm inspired by biological ants. This paper defines a variant of
such algorithm to perform colour quantization. Some of the features of the basic Ant-tree …

Short texts clustering is one of the most difficult tasks in natural language processing due to
the low frequencies of the document terms. We are interested in analysing these kind of …

The economic recession in the European countries during the current financial crisis and the
widespread worsening of the financial situation have resulted in wide macroeconomic …

This paper utilizes neural network map** technology to assess the dynamic nature of
systemic risk over time in the banking industry. We combine the nonparametric method of …

Severe financial crises have periodically battered global economies in recent decades
(Laeven and Valencia, 2012). Crisis periods manifest waves of bank insolvencies, declines …