About the Knowledge Engineering Group
The Knowledge Engineering Group (KEG) is an informal research meta-group at the University of Economics, Prague. It overarches the research activities of the Department of Information and Knowledge Engineering (DIKE), i.e. of its four recently formed workgroups having their own websites:
- DMKD - Data Mining and Knowledge Discovery
- SWOE - Semantic Web and Ontological Engineering
- IIS - Intelligent Information Systems
- WELT - Web Engineering and Library Technology
Most of the KEG website is no longer updated and reflects the situation in 2008. Regularly updated is however the log of group highlights (the 10 most recent being in the News section below) and the calendar of KEG seminars (including the abstracts and slides of talks). Other kinds of information are assumed to appear at the workgroup websites.
- Towards an Artificially Intelligent System: Evaluating the Intelligence of an Artificial System: Ondřej Vadinský (KIZI VŠE Praha)
- Special smart room for patients with specific disabilities: Jiří Zumr (KIZI VŠE Praha)
- 2016-10-16: A new PhD student, Jiří Zettel, is joining the group. He will be supervised by prof. Petr Berka and his topic will be related to data pre-processing for data mining.
- 2016-10-04: Tomáš Kliegr will give talk on association rule classification and the EasyMiner system developed by the DMKD group at the IEEE Days at the University of West Bohemia. See also: EasyMiner homepage
- 2016-09-22: pon invitation of V. Svátek, Steffen Staab is coming to give a talk at the Prague Computer Science seminar. See also: http://praguecomputerscience.cz/index.php?l=en&p=22
- 2016-09-20: Stanislav Vojíř has successfuly defended his PhD thesis “Business Rule Learning using data mining of GUHA association rules”. He remains member of our team.
- 2016-09-12 – 2016-09-16: We and a few collaborating groups enjoyed a visit of Giancarlo Guizzardi from UFES, Brazil, who among other gave a talk at the KEG seminar, and collaboration plans have been set. See also: http://www.inf.ufes.br/~gguizzardi/, http://keg.vse.cz/seminar.php?datetime=2016-09-15
- 2016-09-01: The article An ontological investigation over human relations in linked data (by Miroslav Vacura, Vojtěch Svátek and Aldo Gangemi) will appear in Applied Ontology. See also: http://content.iospress.com/articles/applied-ontology/ao169
- 2016-08-01: The article Adapting ontologies to best-practice artifacts using transformation patterns: Method, implementation and use cases (by Vojtěch Svátek, Marek Dudáš and Ondřej Zamazal) is online in Journal of Web Semantics. See also: http://www.sciencedirect.com/science/article/pii/S1570826816300336
- 2016-08-01: The LHD dataset developed by our group is available for download as part of the DBpedia 2015 release. See also: LHD dataset page, http://wiki.dbpedia.org/Downloads2015-10
- 2016-06-01: A new paper by Tomáš Kliegr (and Ondřej Zamazal): LHD 2.0: A text mining approach to typing entities in knowledge graphs is just online in Elsevier’s Journal of Web Semantics. It follows up with the recent LHD paper in the same journal. See also: http://www.sciencedirect.com/science/article/pii/S1570826816300166, http://www.sciencedirect.com/science/article/pii/S1570826814001048
- 2016-06-01: Ondřej Zamazal co-authored an article (first author is Tomáš Kliegr from the DMKD group): LHD 2.0: A text mining approach to typing entities in knowledge graphs, now published online in Journal of Web Semantics. See also: http://kizi.vse.cz/english/science/research-group-data-mining-and-knowledge-discovery-dmkd/, http://www.sciencedirect.com/science/article/pii/S1570826816300166
Complete list of history is available as well.
Selected research demos
|EasyMiner - mining rich associations from data using a web interface|
|LISp-Miner - stand-alone tool for rich association discovery|
|THD - targeted hypernym discovery, using Wikipedia articles in a live setting|
|PatOMat tools - a collection of tools enabling pattern-based ontology transformation (within the OWL language) and related tasks|
Visit us at our office NB 413, find location by Foursquare venue.