Title :
Reasoning with Imprecise Context Using Improved Dempster-Shafer Theory
Author :
Lyu, Chang Hoon ; Choi, Min Seok ; Li, Zhong Yuan ; Youn, Hee Yong
Author_Institution :
Sch. of Inf. & Commun. Eng., Sungkyunkwan Univ., Suwon, South Korea
fDate :
Aug. 31 2010-Sept. 3 2010
Abstract :
In pervasive computing environment the contexts are usually imprecise and incomplete due to unreliable connectivity, user mobility, and resource constraints. In this paper we present an approach based on the Dempster-Shafer Theory (DST) for the reasoning with imprecise context. To solve the two fundamental issues of the DST, computation intensiveness and the Zadeh paradox, we filer out excrescent subsets based on their energy to reduce the number of subsets, and employ the concept of evidence loss and approval degree of evidence in the combining process.
Keywords :
inference mechanisms; set theory; ubiquitous computing; uncertainty handling; Zadeh paradox; computation intensiveness; excrescent subset; imprecise context; improved Dempster-Shafer theory; pervasive computing; Cognition; Computational modeling; Context; Hidden Markov models; Pervasive computing; Reliability; Sensors; Context reasoning; Demspter-Shafer theory; evidence theory; pervasive computing;
Conference_Titel :
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2010 IEEE/WIC/ACM International Conference on
Conference_Location :
Toronto, ON
Print_ISBN :
978-1-4244-8482-9
Electronic_ISBN :
978-0-7695-4191-4
DOI :
10.1109/WI-IAT.2010.190