Context-Aware Service Adaptation via Learning Classifier System with Co-evolutionary Mechanism

Shangguang Wang, Zibin Zheng, Guoqiang Li, Hua Zou, Fangchun Yang
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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.
基于协同进化机制的学习分类器系统的上下文感知服务适应
本文提出了一种基于协同进化机制的学习分类器系统,用于上下文感知移动服务自适应中获取准确的用户偏好信息。我们的系统可以生成新用户的初始分类器种群,以加快其收敛速度,并帮助当前用户预测与未覆盖的上下文相对应的动作。实验结果表明了该系统对移动业务适应的效率和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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