Abstract The application of data mining algorithms needs a goal-oriented preprocessing of the data. In practical applications the preprocessing task is very time consuming and has ...
With increasing complexity of manufacturing processes, the volume of data that has to be evaluated rises accordingly. The complexity and data volume make any kind of manual data a...
Peter Benjamin Volk, Martin Hahmann, Dirk Habich, ...
Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...
Real-time data services can benefit data-intensive real-time applications, e.g., e-commerce, via timely transaction processing using fresh data, e.g., the current stock prices. T...
Sampling has been recognized as an important technique to improve the efficiency of clustering. However, with sampling applied, those points which are not sampled will not have t...