Journal article
Extending data mining methodologies to encompass organizational factors
Systems Research and Behavioral Science, Vol.24(2), pp.183-190
2007
Abstract
Data mining has been applied to a wide range of applications in its relatively short existence, but much of the research to date has concentrated upon its more technical and algorithmic aspects at the expense of the overall system; existing methodologies are primarily guidelines for data mining specialists. This study aims to redress the balance by producing a new theoretical framework incorporating key systemic and contextual factors. The framework represents a new way of thinking about data mining, and can be used to reduce the number of projects that are technically sound but of little or no organizational benefit. Further, the framework strengthens the theoretical underpinnings of data mining by identifying essential systemic factors at every stage of the data mining process.
Details
- Title
- Extending data mining methodologies to encompass organizational factors
- Authors
- Justin Debuse (Author) - University of the Sunshine Coast - Faculty of Business
- Publication details
- Systems Research and Behavioral Science, Vol.24(2), pp.183-190
- Publisher
- John Wiley & Sons Ltd.
- Date published
- 2007
- DOI
- 10.1002/sres.823
- ISSN
- 1092-7026; 1092-7026
- Organisation Unit
- University of the Sunshine Coast, Queensland
- Language
- English
- Record Identifier
- 99449550602621
- Output Type
- Journal article
Metrics
7 File views/ downloads
480 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Web Of Science research areas
- Management
- Social Sciences, Interdisciplinary