Improving the Effectiveness of Child Welfare Management using a Knowledge Discovery System

By:
Dr. Bay Arinze,
Murugan Anandarajan
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This proposal advances an innovative information technology-based solution to alert child welfare workers to potential problems with children under their care. It will help them to make more effective decisions, reduce costs, find administrative economies, and improve service levels in the long run. Specifically the information system, Child Welfare Knowledge Discovery System (CWKDS) will use neural networks, genetic algorithms, and support vector machines to explore and analyze large data sets i.e., child welfare data. These artificial intelligence based techniques are effective in detecting previously unknown patterns in the data. This use of knowledge discovery would help address the concerns of welfare workers that the sheer size of their data and the consequent difficulties in analyzing them has resulted in negative and sometimes, tragic consequences.


Keywords: Child Welfare, Artificial Intelligence, Data Mining, Knowledge Discovery
Stream: Technology in Community
Presentation Type: Paper Presentation in English
Paper: A paper has not yet been submitted.


Dr. Bay Arinze

Professor, Management Department, Drexel University
USA


Murugan Anandarajan

Associate Professor, Management Department, Drexel University
USA


Ref: T05P0105