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A Weighted Approach to Partial Matching for Mobile Reasoning

机译:移动推理部分匹配的加权方法

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Due to significant improvements in the capabilities of small devices such as PDAs and smart phones, these devices can not only consume but also provide Web Services. The dynamic nature of mobile environment means that users need accurate and fast approaches for service discovery. In order achieve high accuracy semantic languages can be used in conjunction with logic reasoners. Since powerful broker nodes are not always available (due to lack of long range connectivity), create a bottleneck (since mobile devices are all trying to access the same server) and single point of failure (in the case that a central server fails), on-board mobile reasoning must be supported. However, reasoners are notoriously resource intensive and do not scale to small devices. Therefore, in this paper we provide an efficient mobile reasoner which relaxes the current strict and complete matching approaches to support anytime reasoning. Our approach matches the most important request conditions (deemed by the user) first and provides a degree of match and confidence result to the user. We provide a prototype implementation and performance evaluation of our work.
机译:由于PDA和智能手机等小型设备的功能的显着改进,这些设备不仅可以消耗,而且提供Web服务。移动环境的动态性质意味着用户需要准确和快速的服务发现方法。为了实现高精度语言,可以与逻辑推理使用者一起使用。由于强大的代理节点并不总是可用的(由于缺乏长距离连接),创建瓶颈(由于移动设备都尝试访问相同的服务器)和单点故障(在中央服务器失败的情况下),必须支持车载移动推理。然而,推理师是臭名昭着的资源密集型,并不缩放到小型设备。因此,在本文中,我们提供了一种有效的移动推理,可以放松当前的严格和完整的匹配方法,以支持任何时候推理。我们的方法首先匹配最重要的请求条件(由用户认为)并为用户提供一定程度的匹配和置信结果。我们提供了我们工作的原型实施和绩效评估。

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