Title :
Context-Aware Service Adaptation via Learning Classifier System with Co-evolutionary Mechanism
Author :
Wang, Shangguang ; Zheng, Zibin ; Li, Guoqiang ; Zou, Hua ; Yang, Fangchun
Author_Institution :
State Key Lab. of Networking & Switching Technol., Beijing Univ. of Posts & Telecommun., Beijing, China
Abstract :
In this paper, we propose a novel learning classifier system with the cooperative co-evolutionary mechanism to obtain accurate user preference information in context-aware mobile service adaptation. Our system can generate new user´s initial classifier population to accelerate its converging speed and also help the current user to predict the action corresponding to an uncovered context. Experimental results show the efficiency and effectiveness of our system for mobile service adaptation.
Keywords :
learning (artificial intelligence); mobile computing; pattern classification; context-aware mobile service adaptation; cooperative co-evolutionary mechanism; learning classifier system; preference information; Acceleration; Accuracy; Context; Context-aware services; Mobile communication; Prediction algorithms; Training; Co-evolution; Learning Classifier System; User context; eXtended Classifier System;
Conference_Titel :
Services Computing (SCC), 2012 IEEE Ninth International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4673-3049-7