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    Genetic-PSO fuzzy data mining with divide and conquer strategy

    , Article Proceedings of the 2011 International Conference on Artificial Intelligence, ICAI 2011, 18 July 2011 through 21 July 2011 ; Volume 2 , July , 2011 , Pages 725-729 ; 9781601321855 (ISBN) Jourabloo, A ; Sharif University of Technology
    2011
    Abstract
    Nowadays, discovery the association rules is an important and controversial area in data mining research studies. These rules, describe noticeable association relationships among different attributes. While most studies have focused on binary valued transaction data, in real world applications, there data usually consist of quantitative values. With that in mind, in this paper, we propose a fuzzy data mining algorithm for extracting membership functions from quantitative transactions. This is a hybrid genetic-pso algorithm for finding membership functions suitable for mining problems by a strong cooperation of GA and PSO. This algorithm integrates the two techniques entire run of simulation... 

    Data quality improvement using fuzzy association rules

    , Article ICEIE 2010 - 2010 International Conference on Electronics and Information Engineering, Proceedings, 1 August 2010 through 3 August 2010 ; Volume 1 , August , 2010 , Pages V1468-V1472 ; 9781424476800 (ISBN) Ghorbanpour Alizamini, F ; Pedram, M. M ; Alishahi, M ; Badie, K ; Sharif University of Technology
    2010
    Abstract
    The activities and decisions of organizations and companies are based on data and the information obtained from data analysis. Data quality plays a crucial role in data analysis, because the incorrect data leads to wrong decisions. Nowadays, improving the data quality manually is very difficult and in many cases is impossible as data quality is one of the complicated and non-structured concepts and data refinement process can not be done without the help of professional domain experts, and detection and correction of errors require a thorough knowledge in the related domain of the data. Thus, the necessity of using (semi-)automatic methods is discussed to find data defects and errors and...