Data clustering methods have many applications in the area of data mining. Traditional clustering algorithms deal with quantitative or categorical data points. However, there exist...
Tadeusz Morzy, Marek Wojciechowski, Maciej Zakrzew...
Partitioning a large set of objects into homogeneous clusters is a fundamental operation in data mining. The k-means algorithm is best suited for implementing this operation becau...
Data mining techniques, in spite of their benefit in a wide range of applications have also raised threat to privacy and data security. This paper addresses the problem of preservi...
S. Srinivasa Rao 0002, K. V. S. V. N. Raju, P. Kus...
Abstract. The concept of similarity is fundamentally important in almost every scientific field. Clustering, distance-based outlier detection, classification, regression and sea...
— This paper introduces a quantitative method for social data analysis, which is based on the use of categorical data clustering. More specifically, we employ categorical data cl...