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Conference Paper
Age-Group Classification for Family Members Using Multi-Layered Bayesian Classifier with Gaussian Mixture Model
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- Authors
- Chuho Yi, Seungdo Jeong, Kyeong-Soo Han, Hankyu Lee
- Issue Date
- 2013-05
- Citation
- International Conference on Multimedia and Ubiquitous Engineering (MUE) 2013 (LNEE 240), v.240, pp.1153-1159
- Publisher
- Springer
- Language
- English
- Type
- Conference Paper
- Abstract
- This paper proposes a TV viewer age-group classification method for family members based on TV watching history. User profiling based on watching history is very complex and difficult to achieve. To overcome these difficulties, we propose a probabilistic approach that models TV watching history with a Gaussian mixture model (GMM) and implements a feature-selection method that identifies useful features for classifying the appropriate age-group class. Then, to improve the accuracy of age-group classification, a multi-layered Bayesian classifier is applied for demographic analysis. Extensive experiments showed that our multi-layered classifier with GMM is valid. The accuracy of classification was improved when certain features were singled out and demographic properties were applied. © 2013 Springer Science+Business Media Dordrecht(Outside the USA).
- KSP Keywords
- Age group, Bayesian Classifier, Classification method, Demographic Analysis, Family members, Feature selection(FS), Gaussian mixture Model(GMM), Probabilistic approach, Selection method, User Profiling, group classification