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Towards Semantically Enabled Complex Event Processing

機譯：走向語義啟用的復(fù)雜事件處理

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The Semantic Web provides a framework for semantically annotating data on the web, and the Resource Description Framework (RDF) supports the integration of structured data represented in heterogeneous formats. Traditionally, the Semantic Web has focused primarily on more or less static data, but information on the web today is becoming increasingly dynamic. RDF Stream Processing (RSP) systems address this issue by adding support for streaming data and continuous query processing. To some extent, RSP systems can be used to perform complex event processing (CEP), where meaningful high-level events are generated based on low-level events from multiple sources; however, there are several challenges with respect to using RSP in this context. Event models designed to represent static event information lack several features required for CEP, and are typically not well suited for stream reasoning. The dynamic nature of streaming data also greatly complicates the development and validation of RSP queries. Therefore, reusing queries that have been prepared ahead of time is important to be able to support real-time decision-making. Additionally, there are limitations in existing RSP implementations in terms of both scalability and expressiveness, where some features required in CEP are not supported by any of the current systems. The goal of this thesis work has been to address some of these challenges and the main contributions of the thesis are: (1) an event model ontology targeted at supporting CEP; (2) a model for representing parameterized RSP queries as reusable templates; and (3) an architecture that allows RSP systems to be integrated for use in CEP. The proposed event model tackles issues specifically related to event modeling in CEP that have not been sufficiently covered by other event models, includes support for event encapsulation and event payloads, and can easily be extended to fit specific use-cases. The model for representing RSP query templates was designed as an extension to SPIN, a vocabulary that supports modeling of SPARQL queries as RDF. The extended model supports the current version of the RSP Query Language (RSP-QL) developed by the RDF Stream Processing Community Group, along with some of the most popular RSP query languages. Finally, the proposed architecture views RSP queries as individual event processing agents in a more general CEP framework. Additional event processing components can be integrated to provide support for operations that are not supported in RSP, or to provide more efficient processing for specific tasks. We demonstrate the architecture in implementations for scenarios related to traffic-incident monitoring, criminal-activity monitoring, and electronic healthcare monitoring.
機譯：語義Web提供了一個用于在Web上語義注釋數(shù)據(jù)的框架，而資源描述框架（RDF）支持以異構(gòu)格式表示的結(jié)構(gòu)化數(shù)據(jù)的集成。傳統(tǒng)上，語義Web主要集中于或多或少的靜態(tài)數(shù)據(jù)，但是當(dāng)今Web上的信息正變得越來越動態(tài)。 RDF流處理（RSP）系統(tǒng)通過添加對流數(shù)據(jù)和連續(xù)查詢處理的支持來解決此問題。在某種程度上，RSP系統(tǒng)可用于執(zhí)行復(fù)雜事件處理（CEP），其中基于來自多個來源的低級事件生成有意義的高級事件；但是，在這種情況下使用RSP存在一些挑戰(zhàn)。設(shè)計用于表示靜態(tài)事件信息的事件模型缺少CEP所需的幾個功能，并且通常不太適合流推理。流數(shù)據(jù)的動態(tài)性質(zhì)也極大地簡化了RSP查詢的開發(fā)和驗證。因此，重用事先準(zhǔn)備好的查詢對于支持實時決策很重要。此外，在現(xiàn)有RSP實現(xiàn)中，就可伸縮性和可表達(dá)性而言存在局限性，其中任何當(dāng)前系統(tǒng)都不支持CEP中所需的某些功能。論文工作的目的是解決其中的一些挑戰(zhàn)，并且論文的主要貢獻(xiàn)是：（1）針對支持CEP的事件模型本體； （2）將參數(shù)化的RSP查詢表示為可重用模板的模型； （3）允許集成RSP系統(tǒng)以在CEP中使用的體系結(jié)構(gòu)。提議的事件模型解決了與CEP中的事件建模特別相關(guān)的問題，而其他事件模型并未充分解決這些問題，包括對事件封裝和事件有效負(fù)載的支持，并且可以輕松擴展以適合特定的用例。表示RSP查詢模板的模型被設(shè)計為SPIN的擴展，SPIN是支持將SPARQL查詢建模為RDF的詞匯表。擴展模型支持由RDF流處理社區(qū)組開發(fā)的當(dāng)前版本的RSP查詢語言（RSP-QL），以及一些最受歡迎的RSP查詢語言。最后，提出的體系結(jié)構(gòu)將RSP查詢視為更通用的CEP框架中的單個事件處理代理?？梢约善渌录幚斫M件，以為RSP中不支持的操作提供支持，或為特定任務(wù)提供更有效的處理。我們在與交通事件監(jiān)視，犯罪活動監(jiān)視和電子醫(yī)療監(jiān)視有關(guān)的場景的實現(xiàn)中演示了該體系結(jié)構(gòu)。

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    Keskis?rkk?, Robin;

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  • 年度 2017
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  • 正文語種 eng
  • 中圖分類

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