Data Mining
Data Mining
Many applications, e.g., in biomedicine, the web and sensor networks generate tremendous amounts of data. We have unprecedented opportunities to find profound answers to complex questions, e.g., "what is the best way to get to the airport?" Or: "is this drug suitable for me?" However, having more data not automatically means gaining more knowledge.
To exploit the opportunities in Big Data, we need intelligent and efficient algorithms translating the information in data into understandable knowledge. The research group Data Mining headed by Prof. Dr. Claudia Plant investigates methods comprehensively supporting the process of knowledge discovery from Big Data.
Currently, we focus on the following topics:
- Information-theoretic data mining, e.g. graph representation learning
- Clustering, e.g. clustering of high-dimensional data with deep autoencoders
- Algorithms for complex data: graphs, time series and heterogeneous data, e.g. for attributed multi-graphs (KDD 2021 Student Best Paper Award)
- High-performance data mining on parallel hardware, e.g. similarity join on multi-core processors
- Application-related approaches, e.g. with partners from neuroscience, meteorology, transport and particle physics
We are currently contributing to the following projects:
- Learning Synchronization Patterns in Neural Signal
- Digitize! Computational Social Sciences
- Teaching Digital Thinking
- Transparent and Explainable Models
- MEDEA: Meteorologically induced extreme event detection for renewable energy using data-driven methods: from weather prediction to climate time scales
- Knowledge-Infused Deep Learning for Natural Language Processing (in the role of the host)
- CLU-Smart: Clustering of Smart-Meter Data
Current members of the Data Mining group:
- Prof. Dr. Claudia Plant
- Dr. Anna Beer
- Dr. Katerina Schindlerova
- Can Altinigneli (co-supervised with Christian Böhm)
- Lena Bauer (co-supervised with Philipp Grohs)
- Guojun Lai
- Maximilian Leodolter
- Lukas Miklautz
- Pranava Mummoju (co-supervised with Christian Böhm)
- Ylli Sadikaj
- Martin Teuffenbach
- Pascal Weber
Guests:
- Prof. Peter Dolog
- Zhaoliang Chen