Effective appliance selection by complementary context feeding in smart home system

Authors:
Taek Lee;Jiyong Park;Hoh Peter In
Affiliations:
Department of Computer Science and Engineering, Korea University, Seoul, Republic of Korea;Department of Computer Science and Engineering, Korea University, Seoul, Republic of Korea;Department of Computer Science and Engineering, Korea University, Seoul, Republic of Korea
Venue:
SEUS'07 Proceedings of the 5th IFIP WG 10.2 international conference on Software technologies for embedded and ubiquitous systems
Year:
2007

Citing 8
Cited 0

Data mining: concepts and techniques

Data mining: concepts and techniques
Development of Situation-Aware Application Software for Ubiquitous Computing Environment

COMPSAC '02 Proceedings of the 26th International Computer Software and Applications Conference on Prolonging Software Life: Development and Redevelopment
Multimodal interfaces

The human-computer interaction handbook
Situation-Aware Contract Specification Language for Middleware for Ubiquitous Computing

FTDCS '03 Proceedings of the The Ninth IEEE Workshop on Future Trends of Distributed Computing Systems
An FSM model for situation-aware mobile application software systems

ACM-SE 42 Proceedings of the 42nd annual Southeast regional conference
Introduction to Data Mining, (First Edition)

Introduction to Data Mining, (First Edition)
Conflict Resolution Model Based on Weight in Situation Aware Collaboration System

FTDCS '07 Proceedings of the 11th IEEE International Workshop on Future Trends of Distributed Computing Systems
Context-Aware Computing Applications

WMCSA '94 Proceedings of the 1994 First Workshop on Mobile Computing Systems and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

Smart Home System (SHS) is one of popular applications in ubiquitous computing, which provides convenient services for a user with userfriendly intelligent system interfaces. Among them, voice recognition is a popular interface. However, voice command statements given by users are often too unclear and incomplete for the devices in SHS to understand the original user intention. So, the devices become complicated and have no idea about whether to work or not. Therefore, we should make sure the proximate selection for the devices which will be eventually targeted and operated following user intention. In this paper, we propose an effective method to make a decision in electing a promising target device among candidates by taking advantage of complementary context feeding around user environment in SHS even with initial incomplete interface information. The proposed method is based on Bayes theorem using the way of empirical statistic inference.