Machine learning, data mining and knowledge engineering

Screen shot

Text mining aims at finding hidden patterns in text or hypertext data. It contains knowledge discovery - like clusters, classifiers, association rules or rare events - in text documents as well as in linked data like web or social networks.


Main research areas

  • Text categorization
  • Information extraction
  • Linked data mining
  • Inductive logic programming for text mining
  • Stream data mining
  • Pre-processing for text mining

Research team

Staff:
Eva Mráková

PhD students:
Petr Glos (spatio-temporal data mining), Petr Kosina (stream mining, now in Porto), Jaroslav Bayer, Jan Géryk (mining in IS MU), Šimon Suchomel (text mining)

Students:
Juraj Hreško (classification of web pages), Juraj Jurčo (Information extraction from www, now in Porto), Jan Knotek (Information extraction from www), Jindřich Tandler (mining in social networks)


Knowledge Discovery Lab FI MU

Research in KD lab focuses on theory of inductive inference for learning from various data (multirelational, text, biomedical, streams) and to applications (spatio-temporal data, educational data). See lab pages for more information.

KD Lab tightly collaborates with INESC-LIAAD Porto and Universidade do Porto.


Contact

Luboš Popelínský
popel (somewhere at) fi [muni] cz
www.fi.muni.cz/~popel/
B418 FI MU