In this paper we address the problem of combining multiple clusterings without access to the underlying features of the data. This process is known in the literature as clustering...
Consensus clustering is the problem of reconciling clustering information about the same data set coming from different sources or from different runs of the same algorithm. Cast ...
Consensus clustering and semi-supervised clustering are important extensions of the standard clustering paradigm. Consensus clustering (also known as aggregation of clustering) ca...
Combining multiple clusterings arises in various important data mining scenarios. However, finding a consensus clustering from multiple clusterings is a challenging task because ...
Abstract. A major problem encountered by text clustering practitioners is the difficulty of determining a priori which is the optimal text representation and clustering technique f...