The Institute of Computer Science

Article index

  1. The Institute's research areas
  2. Recent research results
  3. Selected research projects
  4. Scientific characteristics

In recent years the most important research results are related mostly to:

  1. Data mining and knowledge discovery
  2. Software quality assessment and software testing

In the area of knowledge discovery the following new methods and algorithms have been created:

  • New highly efficient method (GDFLR-SO-Apriori) of discovery of frequent patterns with negation. The new method reduces redundant computations via introduction of such ordering of pattern variants, that allows reuse of partial computation results. It has been experimentally proven that this new method is up to 100 times faster than older GDFLR-Apriori algorithm.
  • Some improvements in clustering algorithms DBSCAN and FIHC have been developed,
  • Spatial data exploration algorithms have been proposed and evaluated.
  • New methodology of ontology management and building basing on exploratory approach to textual data has been created. Towards this end some new algorithms for extraction of useful ontology related data from natural language based sources have been implemented (such as taxonomy, synonymy and homonymy discovery, tems association analysis etc.). New data exploration algorithms T-FIHC and T-GSP have been created, that are highly optimized for processing of large amounts of heterogeneous textual data.

Some important accomplishments  related to software testing include:

  • development of new, efficient methods incorporating software mutation techniques and aspect driver programming;
  • development of methods and an environment for software modeling and verification, with special emphasis on embedded systems.