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A context-aware middleware for real-time semantic enrichment of distributed multimedia metadata

机译:一种上下文感知的中间件,用于分布式多媒体元数据的实时语义丰富

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摘要

This paper investigates the problem of the real-time integration and processing of multimedia metadata collected by a distributed sensor network. The discussed practical problem is the efficiency of the technologies used in creating a Knowledge Base in real-time. Specifically, an approach is proposed for the realtime, rule-based semantic enrichment of lower level context features with higher-level semantics. The distinguishing characteristic is the provision of an intelligent middleware-based architecture on which low level components such as sensors, feature extraction algorithms, data sources, and high level components such as application-specific ontologies can be plugged. Throughout the paper, Priamos, a middleware architecture based on Semantic Web technologies is presented, together with a stress-test of the system's operation under two test case scenarios: A smart security surveillance application and a smart meeting room application. Performance measurements are conducted and corresponding results are exposed.
机译:本文研究了分布式传感器网络收集的多媒体元数据的实时集成和处理问题。讨论的实际问题是实时创建知识库所用技术的效率。具体而言,提出了一种利用高级语义实时,基于规则的低级上下文特征语义丰富的方法。显着特点是提供了一种基于智能中间件的体系结构,可以在该体系结构上插入低级组件(例如传感器,特征提取算法,数据源)和高级组件(例如专用本体)。在整个论文中,将介绍Priamos(一种基于语义Web技术的中间件体系结构),以及在两种测试用例场景下对系统运行的压力测试:智能安全监控应用程序和智能会议室应用程序。进行性能测量并暴露相应的结果。

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