Distributed and Parallel Databases

Graph pattern mining aims at identifying structures that appear frequently in large graphs, under the assumption that frequency signifies importance. In real life, there are many graphs with weights on nodes and/or edges. For these graphs, it is ...

In recent years, several applications have emerged which require access to consolidated information that has to be computed and provided in near real-time. Traditional record linkage algorithms are unable to support such time-critical applications,...

Sequential pattern matching to detect a user-defined sequence of conditions on event streams is a key feature in modern event processing systems. However, the sequential nature of event based pattern matching has two major deficiencies. First, it ...

Estimating dependencies from data is a fundamental task of Knowledge Discovery. Identifying the relevant variables leads to a better understanding of data and improves both the runtime and the outcomes of downstream Data Mining tasks. Dependency ...

In this work, we study the problem of maintaining basic aggregate statistics over a sliding-window data stream under the constraint of limited memory. As in IoT scenarios the available memory is typically much less than the window size, queries ...$\mathrm{}$

In order to conduct research effectively, scientists must be able to access, organize, describe, and produce data as part of their daily research activities. While relational databases are well suited to the tasks of describing and organizing ...