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Research on Caching Strategy in a VoiceXML-Based Mobile Learning System

机译:基于VoiceXML的移动学习系统中的缓存策略研究

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摘要

In order to push the new voice-based mobile learning service more quickly and better and decrease the operating risk, employing the technology of the Voice eXtensible Markup Language (VoiceXML) as the service logic language, an independent VoiceXML-based Mobile Learning System (VMLS) is built, its hardware and software system structure design is achieved. The system will be open to course content providers and enable them to provide more new services to students. In the meantime, aiming to the network delay, the key problem existing in VMLS, an adaptive Markov prefetching algorithm shared by multi-users and a more efficient caching replacement strategy are provided, which can improve the forecasting accuracy rate and the overall performance of cache system. The research results are not only used in VMLS, and are also useful the other voice-based application system and the other related research fields.
机译:为了更快,更好地推动基于语音的新移动学习服务,并降低操作风险,采用语音可扩展标记语言(VoiceXML)的技术作为服务逻辑语言,即独立的基于VoiceXML的移动学习系统(VMLS) )建成后,就完成了其硬件和软件系统的结构设计。该系统将向课程内容提供商开放,并使他们能够为学生提供更多新服务。同时针对网络时延,提供了VMLS中存在的关键问题,多用户共享的自适应马尔可夫预取算法和更有效的缓存替换策略,可以提高预测的准确率和整体缓存性能。系统。研究结果不仅在VMLS中使用,而且对其他基于语音的应用系统和其他相关研究领域也很有用。

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