2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.NE2019
Unsupervised Anomaly Detection in Stream Data with Online Evolving Spiking Neural Networks
Piotr S. Maciąg, Marzena Kryszkiewicz, Robert Bembenik +2
Unsupervised anomaly discovery in stream data is a research topic with many practical applications. However, in many cases, it is not easy to collect enough training data with labe…
cs.DB2017
Discovering Sequential Patterns in Event-Based Spatio-Temporal Data by Means of Microclustering - Extended Report
Piotr S. Maciąg
In the paper, we consider the problem of discovering sequential patterns from event-based spatio-temporal data. The problem is defined as follows: for a set of event types and…
cs.DB2017★ 2 cited
Efficient Discovering of Top-K Sequential Patterns in Event-Based Spatio-Temporal Data
Piotr S. Maciąg
We consider the problem of discovering sequential patterns from event-based spatio-temporal data. The dataset is described by a set of event types and their instances. Based on the…