With the popularity of mobile services, an effective context-aware mobile service adaptation is becoming more and more important for operators. In this paper, we propose a Co-evolution eXtended Classifier System (CXCS) to perform context-aware mobile service adaptation. Our key idea is to learn user context, match adaptation rule, and provide the best suitable mobile services for users. Different from previous adaptation schemes, our proposed CXCS can produce a new user's initial classifier population to quicken its converging speed. Moreover, it can make the current user to predict which service should be selected, corresponding to an uncovered context. We compare CXCS based on a common mobile service adaptation scenario with other five adaptation schemes. The results show the adaptation accuracy of CXCS is higher than 70% on average, and outperforms other schemes.

中文翻译：

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在移动网络环境中通过协同进化扩展分类器系统进行上下文感知的移动服务适配

随着移动服务的普及，对于运营商而言，有效的情境感知移动服务适配变得越来越重要。在本文中，我们提出了一种协同进化扩展分类器系统（CXCS）以执行上下文感知的移动服务适配。我们的关键思想是学习用户上下文，匹配适应规则，并为用户提供最合适的移动服务。与以前的适应方案不同，我们提出的CXCS可以产生新用户的初始分类器群体，以加快其收敛速度。而且，它可以使当前用户预测应该选择哪个服务，对应于一个未覆盖的上下文。我们将基于常见移动服务适配方案的CXCS与其他五种适配方案进行了比较。结果表明，CXCS的自适应精度平均高于70％，