We propose a hybrid clustering strategy by integrating heterogeneous information sources as graphs. The hybrid clustering method is extended on the basis of modularity based Louva...
Xinhai Liu, Shi Yu, Yves Moreau, Frizo A. L. Janss...
We investigate the following data mining problem from Computational Chemistry: From a large data set of compounds, find those that bind to a target molecule in as few iterations o...
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...
Given a collection of Boolean spatio-temporal(ST) event types, the cascading spatio-temporal pattern (CSTP) discovery process finds partially ordered subsets of event-types whose ...
Pradeep Mohan, Shashi Shekhar, James A. Shine, Jam...
We present a new algorithm for mining maximal frequent itemsets from a transactional database. Our algorithm is especially efficient when the itemsets in the database are very lon...