Research Projects

ICT COST Action IC1302: Semantic Keyword-based Search on Structured Data Sources (KEYSTONE)

Principal Researcher: Prof. Ngoc Thanh Nguyen (representative of Poland and chair of WG4)
Funding Organization: European Commission
Duration: 2013-2016
http://www.keystone-cost.eu/

The Action proposes to join synergies from several disciplines, such as semantic data management, the semantic web, information retrieval, artificial intelligence, machine learning, user interaction, service science, service design, and natural language processing.


Applications of multiagent systems to various processes of knowledge integration and group decision making

Principal Researcher: Professor Ngoc Thanh Nguyen
Funding Organization: Ministry of Science and Higher Education
Program: Young Inventors University
Duration: 2014-2015

The goal of this research project is to develop methods of knowledge integration and group decision making in multiagent systems and to implement this system. Project is realized with cooperation with High School No. III in Wroclaw. Students of this school are working in small groups under the supervision of academic staff of our Department. Effects of each team will be: the implemented multiagent system, the developed methods of knowledge integration, a method knowledge inconsistency processing and quality analysis of the knowledge.


To what extent can design principles for complex networks be derived from the study of error propagation phenomenon in smart and bio-inspired network structures?

Principal Researcher: Dr. Dariusz Król
Funding Organization: European Commission, Marie Curie Action: Intra-European Fellowship
Duration: 2012-2014
http://cordis.europa.eu/project/rcn/101627_en.html

The project under grant FP7-PEOPLE-2010-IEF-274375-EPP has been concerned with the question of whether and to what extent design principles for complex networks can be derived from the study of error propagation phenomena in modern network structures found in biological, transportation and communication systems.
The project resulted, among other things, in preparation and publication of a special issue of the New Generation Computing journal on "Propagation Phenomenon in Complex Networks: Theory and Practice" as well as a comprehensive edited book on "Propagation Phenomena in Real World Networks” to be published by Springer in their Intelligent Systems Reference Library series. Both edited volumes have been meant to bring attention to this very important subject area and attracted an excellent selection of contributions providing a starting point and a reference for future research.



Methods of ontology alignment involving semantics and valuations of ontology concepts

Principal Researcher: Professor Ngoc Thanh Nguyen
Researcher: M.Sc Marcin Pietranik
Funding Organization: National Science Centre
Duration: 2011-2013

The goal of this research project is developing methods of finding mappings between ontologies. The main contribution to this widely discussed topic will be expanding basic building blocks of these structures(which are class' attributes) with explicitly given semantics and incorporating formal criteria of identifying relationships between them into the process of designating valid alignments.


Method of determining a personalized learning scenario in E-Learning systems

Principal Researcher: Professor Ngoc Thanh Nguyen
Funding Organization: Polish Ministry of Science and Higher Education
Duration: 2009-2011

The main goal of this research project is to work out a method for determination of an effective scenario for a student using personalization methods. Next this method will be implemented in an intelligent e-learning system.


Method of knowledge integration in selected problems of collective intelligence

Principal Researcher: Professor Ngoc Thanh Nguyen
Funding Organization: Polish Ministry of Science and Higher Education
Duration: 2009-2012

The main goal of this research project is work out a set of tools for knowledge integration using methods for collective intelligence. The focus of this project is on such aspects that processing inconsistency of knowledge, communication languages in multi-agent environments, recommendation systems, and incomplete data processing.


Modelling Computational Collective Intelligence by Using Consensus Theory

Principal Researcher: Professor Ngoc Thanh Nguyen
Funding Organization: Polish Academy of Science (PAN – Poland) and National Research Foundation (NRF-Korea)
Duration: 2010-2011

The main goal of this bilateral research project is to work out a set of tools for collective intelligence with using Consensus Theory. The focus of this project is on such aspects that processing inconsistency of knowledge in web-based systems and ontology integration.


Multiple model prediction methods for dynamic regression problems

Principal Researcher: Dr. Bogdan Trawiński
Funding Organization: Polish National Science Centre
Duration: 2011-2014

Main goal of the project is to elaborate new models and prediction methods based on multiple model and hybrid approaches. It is planned to work out methods ensuring appropriate balance among four basic criteria: accuracy, stability, interpretability, and efficiency. The criteria are very important in some application areas particularly in long-term valuation, e.g. the valuation of real estate or debt packages purchased and sold on the free market.

Due to the incremental occurrence of data used for generalization learning systems are required to revise their current knowledge as soon as new observations occur. Thus, data instability is an essential issue in the prediction of dynamic regression problems. The aim of the project is to devise methods of evolving and incremental learning for regression problems, which allow for consideration of time variable data characteristics.

There are five principal research areas considered within the project, i.e. evolving fuzzy systems applied to ensemble systems, self-adapting genetic algorithms employed to optimization fuzzy systems, incremental algorithms for ensemble models, multiple model prediction of complex structures (sequences, graphs, and multigraphs), incremental learning using feature subspaces and instance subsamples.


Methods of Data Propagation to Solving Problems of Collective Intelligence

Principal Researcher: Dr. Dariusz Król
Funding Organization: Polish Ministry of Science and Higher Education
Duration: 2010-2011

The main goal of the project is to elaborate the effective methods of data propagation in contemporary web systems and their application to solve selected problems of collective intelligence. Such methods are applied when the subjects constitute autonomous and distributed sources of data (knowledge) and to solve problems the integration of that data (knowledge) is needed. Due to big complexity of up-to-date network systems, such as P2P, social networks or multi-agent systems, nature inspired algorithms, multi-criteria optimization and advanced network programming should be employed.