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A Weighted Approach to Partial Matching for Mobile Reasoning

机译:移动推理中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和智能电话等小型设备的功能得到了显着改善,因此这些设备不仅可以使用,还可以提供Web服务。移动环境的动态性质意味着用户需要准确而快速的服务发现方法。为了实现高精度,可以将语义语言与逻辑推理器结合使用。由于功能强大的代理节点并不总是可用(由于缺乏远程连接),因此要创建瓶颈(由于移动设备都试图访问同一服务器)和单点故障(在中央服务器出现故障的情况下),必须支持车载移动推理。但是,众所周知,推理机占用大量资源,并且无法扩展到小型设备。因此,在本文中,我们提供了一种有效的移动推理机,该推理机放宽了当前严格且完整的匹配方法以支持随时推理。我们的方法首先匹配最重要的请求条件(由用户认为),并向用户提供一定程度的匹配和置信度结果。我们提供了工作的原型实施和性能评估。

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