Investigation of fuzzy data mining methods in large and/or very large databases relying upon fuzzy set based and hedge algebra based approaches to exploit knowledge represented in the form of association rules or classification rules that can be applied in certain pratical socio-economic datasets.

• Theoretical results: On the basis of theoretical research and development of hedge algebras (HAs), some methodological basis is established for the development of some effective data mining algorithms to extract useful knowledge from certain socio-economic databases.
• Application results: A sofware system is constructed to implement the proposed fuzzy data mining algorithms. The obtained software system has been tested to extract fuzzy knowledge from real data sets of some monthly economic reports of Vietnam provided by The information Center of the Ministry of Planing and Investment of Vietnam

Proposed data mining algorithms based on a new theory introduced by a team of IT Institute.

Scientific papers in referred journals

1. Cat Ho Nguyen, Witold Pedrycz, Thai Son Tran, Hai Le Bui, Thang Long Duong, A Hedge Algebra Approach to the design of fuzzy classifiers and fuzzy vibration, Proceeding of the Fifth National Conference on Fundamental and Applied Information Technology Research, 2011, 250-274
2. Cat Ho Nguyen,Witold Pedrycz, Thang Long Duong, Thai Son Tran, A genetic design of linguistic terms for fuzzy rule based classifiers. Inter. Journal of Approximate Reasoning, 54(1),1-21, 01/2013
3. Tran Thai Son, Do Nam Tien, Pham Dinh Phong, Associate rull using hedge algebra approach. Journal of computer Science and Cybernetic, 27(4). 2011, 341-352

Technological products

1. Two reports on the methods based on hedge algebra methodology for extracting fuzzy association rules and classification fuzzy rules
2. Two data mining programs on the CD and the softfware program design and analysis document and the program user guide document.