Hierarchical conceptual clustering has been proven to be a useful data mining technique. Graph-based representation of structural information has been shown to be successful in kn...
—When comparing clustering results, any evaluation metric breaks down the available information to a single number. However, a lot of evaluation metrics are around, that are not ...
Elke Achtert, Sascha Goldhofer, Hans-Peter Kriegel...
Recent work has looked at extending clustering algorithms with instance level must-link (ML) and cannot-link (CL) background information. Our work introduces δ and ǫ cluster lev...
Systems software for clusters typically derives from a multiplicity of sources: the kernel itself, software associated with a particular distribution, site-specific purchased or o...
Ewing L. Lusk, Narayan Desai, Rick Bradshaw, Andre...
Concurrent programs are notorious for containing errors that are difficult to reproduce and diagnose. Two common kinds of concurrency errors are data races and atomicity violation...
Rahul Agarwal, Amit Sasturkar, Liqiang Wang, Scott...