The increasing popularity of social networks has initiated a fertile research area in information extraction and data mining. Although such analysis can facilitate better understan...
Traditional problem determination techniques rely on static dependency models that are difficult to generate accurately in today’s large, distributed, and dynamic application e...
Mike Y. Chen, Emre Kiciman, Eugene Fratkin, Armand...
Until recently, most data integration techniques involved central components, e.g., global schemas, to enable transparent access to heterogeneous databases. Today, however, with t...
Many automated learning procedures lack interpretability, operating effectively as a black box: providing a prediction tool but no explanation of the underlying dynamics that driv...
Cluster analysis is a primary method for database mining. It is either used as a stand-alone tool to get insight into the distribution of a data set, e.g. to focus further analysi...
Mihael Ankerst, Markus M. Breunig, Hans-Peter Krie...