— This paper proposes an algorithm to deal with the feature selection in Gaussian mixture clustering by an iterative way: the algorithm iterates between the clustering and the un...
Providing robust decision support for software engineering (SE) requires the collection of data across multiple contexts so that one can begin to elicit the context variables that...
Daniela Cruzes, Victor R. Basili, Forrest Shull, M...
This paper studies the problem of categorical data clustering, especially for transactional data characterized by high dimensionality and large volume. Starting from a heuristic m...
The identification of clusters, well-connected components in a graph, is useful in many applications from biological function prediction to social community detection. However, ...
Clustering is a common problem in the analysis of large data sets. Streaming algorithms, which make a single pass over the data set using small working memory and produce a cluster...