Some techniques and applications in data mining

Data mining plays a central role in knowledge discovery. It involves applying specific algorithms to extract patterns or rules from data sets in a particular representation. Many researchers in database and machine-learning fields are interested in this new research topic since it offers opportunities to discover useful information and important relevant patterns in large databases, thus helping decision-makers analyze data easily and make good decisions regarding the domains in question. Years of effort in data mining have produced a variety of efficient techniques and applications. In this speech, I would like to present some currently popular and interesting techniques developed in our research group. They include the integration of data mining with soft computing, privacy and ontology. The integration of data mining with soft computing can easily handle quantitative transactions and infer linguistic knowledge. Data mining with privacy can hide some transaction data or rules in the mining process for safety. Using ontology can take domain knowledge into consideration and improve the effectiveness of mining results. Besides, I will also introduce some interesting applications such as knowledge warehouse, Web mining and health care.