We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
Density-based clustering algorithms have recently gained popularity in the data mining field due to their ability to discover arbitrary shaped clusters while preserving spatial pr...
M. Emre Celebi, Y. Alp Aslandogan, Paul R. Bergstr...
In this paper we report experiences on a parallel implementation of a standard cell placement algorithm on a cluster of myrinet connected PCs. The proposed algorithm is based on a...
Faris H. Khundakjie, Patrick H. Madden, Nael B. Ab...
We introduce the problem of cluster-grouping and show that it integrates several important data mining tasks, i.e. subgroup discovery, mining correlated patterns and aspects from c...
: Identifying the promoter regions play a vital role in understanding human genes. This paper presents a new cellular automata based text clustering algorithm for identifying these...