Piotr S. Maciag

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 15

Top Topics

Sequential Patterns

Spatio Temporal Data

Top Venues

Environ. Model. Softw.

Publications

Piotr S. Maciag, Robert Bembenik, Aleksandra Piekarzewicz, Javier Del Ser, Jesus L. Lobo, Nikola K. Kasabov
Effective air pollution prediction by combining time series decomposition with stacking and bagging ensembles of evolving spiking neural networks. Environ. Model. Softw. 170 (2023)
Piotr S. Maciag, Robert Bembenik, Artur Dubrawski
Discovery of crime event sequences with constricted spatio-temporal sequential patterns. J. Big Data 10 (1) (2023)
Piotr S. Maciag, Wojciech Sitek, Lukasz Skonieczny, Henryk Rybinski
A Comparative Study of Short Text Classification with Spiking Neural Networks. FedCSIS (2022)
Piotr S. Maciag, Marzena Kryszkiewicz, Robert Bembenik, Jesus L. Lobo, Javier Del Ser
Unsupervised Anomaly Detection in Stream Data with Online Evolving Spiking Neural Networks. Neural Networks 139 (2021)
Piotr S. Maciag, Robert Bembenik, Artur Dubrawski
Discovery of Crime Event Sequences with Constricted Spatio-Temporal Sequential Patterns. CoRR (2021)
Piotr S. Maciag, Marzena Kryszkiewicz, Robert Bembenik
Online Evolving Spiking Neural Networks for Incremental Air Pollution Prediction. IJCNN (2020)
Piotr S. Maciag, Marzena Kryszkiewicz, Robert Bembenik
Discovery of closed spatio-temporal sequential patterns from event data. KES (2019)
Piotr S. Maciag, Robert Bembenik
A Novel Breadth-first Strategy Algorithm for Discovering Sequential Patterns from Spatio-temporal Data. ICPRAM (2019)
Piotr S. Maciag, Marzena Kryszkiewicz, Robert Bembenik, Jesus L. Lobo, Javier Del Ser
Unsupervised Anomaly Detection in Stream Data with Online Evolving Spiking Neural Networks. CoRR (2019)
Piotr S. Maciag
A Framework for Discovering Frequent Event Graphs from Uncertain Event-based Spatio-temporal Data. ICPRAM (2019)
Piotr S. Maciag, Nikola K. Kasabov, Marzena Kryszkiewicz, Robert Bembenik
Air pollution prediction with clustering-based ensemble of evolving spiking neural networks and a case study for London area. Environ. Model. Softw. 118 (2019)
Piotr S. Maciag
Efficient Discovery of Top-K Sequential Patterns in Event-Based Spatio-Temporal Data. FedCSIS (2018)
Piotr S. Maciag
Efficient Discovering of Top-K Sequential Patterns in Event-Based Spatio-Temporal Data. CoRR (2017)
Piotr S. Maciag
A Survey on Data Mining Methods for Clustering Complex Spatiotemporal Data. BDAS (2017)
Piotr S. Maciag
Discovering Sequential Patterns in Event-Based Spatio-Temporal Data by Means of Microclustering - Extended Report. CoRR (2017)