- Title
- Smokers' characteristics and cluster based quitting rule discovery model for enhancement of government's tobacco control systems
- Creator
- Huda, Shamsul; Yearwood, John; Borland, Ron
- Date
- 2010
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/41187
- Identifier
- vital:4679
- Identifier
- http://aisel.aisnet.org/pacis2010/26
- Abstract
- Discovery of cluster characteristics and interesting rules describing smokers' clusters and the behavioural patterns of smoker's quitting intentions is an important task in the development of an effective tobacco control systems. In this paper, we attempt to determine the characteristics smokers' cluster and simplified rule for predicting smokers' quitting behaviour that can provide feedback to build a scientific evidence-based adaptive tobacco control systems. Standard clustering algorithm groups the data based on there inherent pattern. "From abstract"
- Publisher
- Taipei, Taiwan
- Relation
- Proceedings of the 14th Pacific Asia Conference on Information Systems (PACIS 2010)
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- Tobacco control systems; Smokers' quitting rule; Univariate decision tree; Multivariate decision tree; Rule discovery; Smoker's cluster characteristics
- Full Text
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