Mining massive temporal data streams for significant trends, emerging buzz, and unusually high or low activity is an important problem with several commercial applications. In th...
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
The growing availability of mobile devices produces an enormous quantity of personal tracks which calls for advanced analysis methods capable of extracting knowledge out of massiv...
Non-negative matrix factorization (NMF) has become a standard tool in data mining, information retrieval, and signal processing. It is used to factorize a non-negative data matrix ...
C. Thurau, K. Kersting, M. Wahabzada, and C. Bauck...