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Research group: Intelligent Information Systems (IIS)

Related pages

IIS color among the KIZI groups is red, referring to the outstanding position that intelligent systems have compared to conventional information systems.

News (Fall 2014 – Fall 2016):

  • September 2016: Daniel Vodňanský presented a poster (on graph metrics over ontologies) at the KESW 2016 conference.
  • September 2016: Ondřej Zamazal presented a demo paper on a topic related to Ontology Visualization Tools Recommender (OVTR) at the SEMANTiCS 2016 conference.
  • July 2015: Ondřej Vadinský presented his paper “Towards an Artificially Intelligent System: Possibilities of General Evaluation of Hybrid Paradigm” at the Tenth International Workshop on Neural-Symbolic Learning and Reasoning (NeSy’15) held within IJCAI’15, Buenos Aires.
  • May 2015: Daniel Vodňanský defended his PhD project progress on “Data structures and information metrics” (after first year).
  • November 2014: A full paper on ‘Roadmapping and Navigating in the Ontology Visualization Landscape’, by Marek Dudáš, Ondřej Zamazal and Vojtěch Svátek, has been presented at the EKAW 2014 conference in Linköping. The paper is partly based on the Ontology Visualization Tools Recommender (OVTR) as application of the NEST expert system shell.
  • September 2014: A new PhD student, Daniel Vodňanský, enrolled in September 2014; after some internal optimization, he landed in the PhD team of J. Ivánek and joined the group. He will be working on application of information-theoretic measures on web data representations, and will also cooperate with the SWOE group (information content of ontologies etc.).

Research focus

The Intelligent Information Systems (IIS) group at KIZI (one of its four research groups, overarched by the virtual Knowledge Engineering Group) undertakes research in designing and using intelligent systems and investigating their theoretical grounding. The focal areas of the group currently are:

  • Designing and using logic-based, rule-based and case-based expert system shells and providing them with domain- and task-specific knowledge bases
  • Modelling of uncertainty in information systems (including fuzziness, possibilistic models and information theory)
  • Analyzing the properties of observational calculi applicable on association hypotheses discovered in data using analytical tools
  • Study of relationships and differences between human and computational intelligence
  • Software design for intelligent buildings.

Education and research on Artificial Intelligence has been focal for the Department since several decades (almost since the foundation of its predecessor, Dept. of Scientific and Technical Information in early 1980s). The most important artifact of this early period was the SAK expert system shell, developed under the supervision of J. Ivánek and extensively used both in education and inside deployed intelligent systems. Its particularly strong feature was the possibility to switch between different formal models of uncertainty processing.

A marking moment for the AI research at the Department was the foundation of Laboratory for Intelligent Systems as its ‘research spinoff’ in 1996, under the direction of R. Jiroušek. A large part of AI-focused staff moved their research activities to the lab while keeping their bond to the Department, and new researchers, mainly from the Academy of Science, were hired (including J. Vejnarová). A new focal area then became theoretical research on probabilistic and possibilistic models of uncertainty processing. At the same time, the laboratory continued the practice-oriented stream, with the development of tools such as the WISECON system for intelligent support for selecting a computer product in an on-line catalogue (based on Bayesian networks).

After 2000 the research became more diversified. Theoretical research on uncertain reasoning continued. At the same time, a modern implementation of classical expert system shell combining the rule-based and case-based approach appeared under the name of NEST. Further topics (such as agent-based simulation of economic phenomena, principles of hybrid intelligence or intelligent buildings) have been brought in by PhD students.

The research has/had been supported by several research projects, most notably by the long-term research project (2007-2013) funded by the Ministry of Education under no. MSM 6138439910.

Team

Group leaders: Petr Berka, Jiří Ivánek

Other group members (incl. PhD and MSc students): Jiřina Vejnarová, Ondřej (Šváb) Zamazal, Ondřej Vadinský, Daniel Vodňanský, Jiří Zumr, Jan Burian

Collaborations

Within the University, the IIS group mainly cooperates with

  • The Semantic Web and Ontological Engineering (SWOE) group within the same department. In particular, SWOE applies the knowledge representation and reasoning techniques relevant to IIS, including description logics reasoning and rule-based / case-based reasoning (such as the NEST shell).
  • The Data Mining and Knowledge Discovery (DMKD) group within the same department: observational calculi as formal grounding for some of the DMKD tools are a part of the IIS research on uncertainty processing.
  • The Cognitive Informatics group (led by prof. Václav Řepa) at the neighboring Dept. of Information Technology. The overlapping interest is in studying the properties of machine/human intelligence.

Within the Czech Republic, there is lasting cooperation with the Institute of Information Theory and Automation (prime affiliation of J. Vejnarová) in the field of uncertainty processing, and recently with the Faculty of Electrical Engineering, CTU, in the field of intelligent buildings.

At the international level the most active contacts are in the semantic web / ontological segment, and partly in the uncertainty processing segment.

Selected recent publications

  • Zamazal O.: Augmenting the Ontology Visualization Tool Recommender: Input Pre-Filling and Integration with the OOSP Ontological Benchmark Builder. In: SEMANTiCS 2016, Posters and Demos.
  • Vadinský O.: Towards an Artificially Intelligent System: Possibilities of General Evaluation of Hybrid Paradigm. In: NeSy’15 at IJCAI’15.
  • Berka P.: Expert (Knowledge-Based) Systems. In:  (Mehdi Khosrow-Pour, ed.) Encyclopedia of  Information  Science  and  Technology,  Third  Edition.  IGI  Global,  2015.  ISBN  978-1-4666-5888-2, 4555-4563.
  • Berka P.: NEST: A Compositional Approach to Rule-Based and Case-Based Reasoning. Advances in Artificial Intelligence, 2011.
  • Ivánek J.: Some Properties of Evaluated Implications Used in Knowledge-based Systems and Data-mining. Journal of Systems Integration, Vol 3, No 3, pp. 17-23 (2012).
  • Ivánek J.: Affiliated Ratio-implicational and Equivalency Data-mining Quantifiers and their Truth Configurations. In: 9th Workshop on Uncertainty Processing.  Univ. of Economics, Prague, ISBN: 978-80-245-1885-5, pp.82-89 (2012)
  • Jiroušek R., Vejnarová J.: Compositional models and conditional independence in evidence theory. International Journal of Approximate Reasoning, 2011, Vol. 52, No. 3.
  • Simou N., Stoilos G., Saathoff C., Nemrava J., Svátek V., Berka P., Tzouvaras V.: Reasoning for Multimedia Analysis. In: Multimedia Semantics – Metadata, Analysis and Interaction. John Wiley, 2011.

Education

Activities of the group are reflected in several courses taught at the University, most notably the MSc level courses:

A specialized Bc level course is:

Finally, there is also a relevant PhD-level course: