Title
Using Semi-Supervised Learning to Build Bayesian Network for Personal Preference Modeling in Home Environment
Abstract
Smart home which understands user's preference and provides right services at right time is the current trend. In this paper, we aim at developing a system which can achieve this objective by using the Bayesian network to model user's preference. Instead of assuming the structure of Bayesian network is invariant, our system interacts with user appropriately to obtain some useful information and we use the semi-supervised learning with these information to both learn and adjust the Bayesian network for modeling the user's preference in a more accurate manner. We can use preference model to provide adequate service in home environment. A simulation and a real home environment are constructed based on the proposed method, and the experiments also show the usefulness.
Year
DOI
Venue
2006
10.1109/ICSMC.2006.384725
SMC
Keywords
Field
DocType
home environment,belief networks,semisupervised learning,smart home,learning (artificial intelligence),home automation,user centred design,personal preference modeling,home computing,user preference modeling,user modelling,bayesian network,semi supervised learning,learning artificial intelligence
Semi-supervised learning,Computer science,Home computing,Home automation,Bayesian network,Preference learning,Artificial intelligence,Invariant (mathematics),User centred design,Machine learning
Conference
Volume
ISSN
ISBN
5
1062-922X
1-4244-0100-3
Citations 
PageRank 
References 
3
0.42
7
Authors
3
Name
Order
Citations
PageRank
Zhiyang Chen1354.35
Chaolin Wu223726.05
Li-Chen Fu31419196.64