The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Randomization has emerged as a useful technique for data disguising in privacy-preserving data mining. Its privacy properties have been studied in a number of papers. Kargupta et ...
In this paper, we devise an efficient algorithm for clustering market-basket data. Different from those of the traditional data, the features of market-basket data are known to b...
Abstract Clustering text data streams is an important issue in data mining community and has a number of applications such as news group filtering, text crawling, document organiza...
The number and complexity of distributed applications has exploded, and to-date, each has had to create its own method for providing diagnostic tools and performance metrics. Thes...