Consensus clustering has emerged as a powerful technique for obtaining better clustering results, where a set of data partitions (ensemble) are generated, which are then combined to obtain a consolidated solution (consensus ...

Consensus clustering and interactive feature selection are very useful methods to extract and manage knowledge from texts. While consensus clustering allows the aggregation of different clustering solutions into a single ...

Clustering is fundamental to understand the structure of data. In the past decade the cluster ensembleproblem has been introduced, which combines a set of partitions (an ensemble) of the data to obtain a singleconsensus ...

Finding communities in networks is a commonly used form of network analysis. There is a myriad of community detection algorithms in the literature to perform this task. In spite of that, the number of community detection ...

Current Genome-wide advancements in Gene chips technology provide in the “Omics (genomics, proteomics and transcriptomics) research”, an opportunity to analyze the expression levels of thousand of genes across multiple ...

Similarity measures for comparing clusterings is an important component, e.g., of evaluating clustering algorithms, for consensus clustering, and for clustering stability assessment. These measures have been studied for ...

In the last decade, mobile applications have gained widespread use through smartphones, it has radically transformed the way people can access and use the media, bringing the internet and many everyday tasks in the palm ...