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Knowledge Engineering Group

Classification Cluj-Napoca Data Mining Information retrieval Knowledge Representation and Reasoning Machine Learning Medical data mining Natural Language Processing Social Network Analysis Text mining

The Knowledge Engineering Group (KEG), lead by Prof. Rodica Potolea, PhD, is addressing problems for knowledge extraction, representation, storage and management that the information era has brought in various segments of human activity due to data overload.

The main fundamental theoretical aspects our group focuses on are: dealing with problem-specific features extraction from both structured data, pre-processing techniques for handling noisy and/or incomplete data, learning from balanced/unbalanced and structured/unstructured data.

 
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