• DocumentCode
    3501629
  • Title

    Evolving effective strategies for enhancing SHG´s using K-mean clustering

  • Author

    Sajeev, B.U. ; Thangavel, K.

  • Author_Institution
    Center for R&D, PRIST Univ., Thanjavoor, India
  • fYear
    2011
  • fDate
    14-16 Dec. 2011
  • Firstpage
    74
  • Lastpage
    81
  • Abstract
    Fast retrieval of relevant information from the databases has always been a significant issue. Different techniques have been developed for this purpose; one of them is Data mining. Clustering analysis is a key and easy tool in data mining and pattern recognition. In this paper K-Mean clustering is used for evaluating the performance of socially and economically backward group of people, self help groups (SHG´s) in Kerala state, and suggestions are made to improve socioeconomic status. The necessary information about the members of SHG has been collected from 9 districts in Kerala through structured questionnaire. The Parameters considered for the study are financial status, types of loan availed, improvement in assets before and after joining the group, effect of joining in more than one group and district wise analysis.
  • Keywords
    data analysis; data mining; pattern clustering; social sciences computing; socio-economic effects; K-means clustering; Kerala state; SHG enhancement; asset improvement; data mining; databases; district wise analysis; economically backward people; financial status; group wise analysis; information retrieval; joining effect; loan availability; pattern recognition; self help group; socially backward people; socioeconomic status; structured questionnaire; Algorithm design and analysis; Clustering algorithms; Computer science; Couplings; Data mining; Economics; Government; Data mining; K-means; SHG;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computing (ICoAC), 2011 Third International Conference on
  • Conference_Location
    Chennai
  • Print_ISBN
    978-1-4673-0670-6
  • Type

    conf

  • DOI
    10.1109/ICoAC.2011.6165152
  • Filename
    6165152