We present a framework for mining association rules from transactions consisting of categorical items where the data has been randomized to preserve privacy of individual transact...
Alexandre V. Evfimievski, Ramakrishnan Srikant, Ra...
As postgenomic biology becomes more predictive, the ability to infer rate parameters of genetic and biochemical networks will become increasingly important. In this paper, we expl...
This paper presents an autonomous algorithm for discovering exception rules from data sets. An exception rule, which is defined as a deviational pattern to a well-known fact, exhi...
Besides the problem of searching for effective methods for extracting knowledge from large databases (KDD) there are some additional problems with handling ecological data, namely ...
Density-based clustering has the advantages for (i) allowing arbitrary shape of cluster and (ii) not requiring the number of clusters as input. However, when clusters touch each o...