Services business generates significant amount of human and machine created data. Search and discovery of relevant information from this data is a critical factor in enhancing wor...
Nithya Rajamani, Murthy V. Devarakonda, Yu Deng, W...
Background: Tight clustering arose recently from a desire to obtain tighter and potentially more informative clusters in gene expression studies. Scattered genes with relatively l...
Fuzzy-clustering methods, such as fuzzy k-means and Expectation Maximization, allow an object to be assigned to multiple clusters with different degrees of membership. However, th...
We propose a new paradigm for building scalable distributed systems. Our approach does not require dealing with message-passing protocols—a major complication in existing distri...
Marcos Kawazoe Aguilera, Arif Merchant, Mehul A. S...
Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity meas...