Clustering, in data mining, is useful to discover distribution patterns in the underlying data. Clustering algorithms usually employ a distance metric based (e.g., euclidean) simi...
As the number of I/O-intensive MPI programs becomes increasingly large, many efforts have been made to improve I/O performance, on both software and architecture sides. On the sof...
The nature of data in enterprises and on the Internet is changing. Data used to be stored in a database first and queried later. Today timely processing of new data, represented ...
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
One of the main factors for the knowledge discovery success is related to the comprehensibility of the patterns discovered by applying data mining techniques. Amongst which we can...