title: Data mining in child welfare.
abstract: Data mining is the sifting through of voluminous data to extract knowledge for decision making. This article illustrates the context, concepts, processes, techniques, and tools of data mining, using statistical and neural network analyses on a dataset concerning employee turnover. The resulting models and their predictive capability, advantages and disadvantages, and implications for decision support are highlighted.
authors.affiliation: University of Texas at Arlington School of Social Work, USA.
authors.forename: D
authors.initials: D
authors.lastname: Schoech
authors.forename: A
authors.initials: A
authors.lastname: Quinn
authors.forename: J R
authors.initials: JR
authors.lastname: Rycraft
mesh_terms: D002648:Child; D002669:Child Welfare / Q000706:statistics & numerical data*; D003660:Decision Support Systems, Management; D006078:Government Programs; D006801:Humans; D016571:Neural Networks, Computer; D010563:Personnel Turnover / Q000706:statistics & numerical data*; D011050:Policy Making; D012947:Social Work; D018511:Systems Integration; D014481:United States; D000078329:Workforce