Dr. Michael Cochez
Contact Information
| Address: |
Lehrstuhl Informatik 5 6011, ground floor, building: E2 Ahornstr. 55 52056 Aachen DE |
| Phone: | +49 241 80 21510 |
| Fax: | +49 241 80 22321 |
| Mobile: | +4915904126533 |
| Email: | cochez@fit.fraunhofer.de |
Online Presence
| Website: | http://www.cochez.nl |
I moved to the Vrije Universiteit Amsterdam.
An up to date list of publications can be found from http://users.jyu.fi/~miselico/research/publications/
I am usually not accepting new supervisions at RWTH.
Past Teaching
Theses
- Exploring Unknown Environments - Finding Pollution in Underground Pipes (Open)
- Dynamic Embeddings of Evolving Knowledge Graphs (Running)
- Graph-Structured Query Construction for Natural Language Questions (Running)
- Machine Learning for Anonymization of Unstructured Text (Running)
- Modeling for Street Level Crime Prediction (Running)
- Privacy Attack on Social Networks Using Network Embeddings (Running)
- Concept embeddings for Wikipedia across language editions (2019)
- Deep Learning-based Knee Osteoarthritis Diagnosis from Radiographs and Magnetic Resonance Images (2019)
- Feature Clustering and Visualization of High Dimensional Data using Clique Cover Theory (2019)
- Including Attributes in a Graph Embedding (2018)
- Semantic Data Profi ling in Data Lake (2018)
- Modeling Evolutionary Algorithm Optimized Autonomous Sensory Agents in ROS (2018)
- The Pragmatics and Logic of Knowledge Representation with Prototypes (2017)
- Prototypes on IPFS: A Realization of globally distributed reusable Knowledge (2017)
- Extending Estimation of Parking Occupancy to Untracked City Areas using City Background Information (2017)
- Go with the Flow - Exponential Decaying Reservoir Sampling of Evolving Data Streams (2017)
- Conversion from RDF to Prototype-based Knowledge Base ()
- Evaluating the performance of all-pairs personalized page rank ()
- Evaluation of Approximate Hierarchical Clustering Algorithms ()
- Accelerating KGlove Graph Embedding ()
- An Editor for Prototype-based Knowledge Bases ()
- Evaluation of Stream Sampling Algorithms ()
- Optimizing Mining Maximal Frequent Patterns with MFPAS ()
- Immutability for Prototype-based Knowledge Bases ()
- Data Dependence and Indecisiveness for Locality-Sensitive Hashing ()
Peter Chen Award 2020 goes to Prof. Matthias Jarke 