Sentinel: A Codesigned Platform for Semantic Enrichment of Social Media Streams
Sentinel: A Codesigned Platform for Semantic Enrichment of Social Media Streams
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DOI：
10.1109/tcss.2017.2763684
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发表时间：
2018-03
影响因子：
5
通讯作者：
A. Preece;Irena Spasic;Kieran Evans;David Rogers;William M. Webberley;C. Roberts;M. Innes
中科院分区：
文献类型：
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作者：
A. Preece;Irena Spasic;Kieran Evans;David Rogers;William M. Webberley;C. Roberts;M. Innes
我们引入了Sentinel平台，该平台支持流媒体社交媒体数据的语义丰富，以实现情景理解的目的。该平台是计算科学家和社会科学家共同设计的结果，通过一系列试点研究迭代开发。该平台是建立在一个基于知识的方法，其中输入流（通道）的特点是空间和术语参数，收集的媒体进行预处理，以确定重要的条款（信号），和数据标记（框架）有关的本体。对加工媒体的解释是根据5W框架（谁，什么，何时，何地，为什么）来构建的。该平台的设计是开放的，以纳入新的处理模块，建立在基于知识的元素（通道，信号和框架本体），并通过一组面向用户的应用程序访问。我们提出了平台的概念架构，讨论了底层流处理系统的设计和实现挑战，并提出了一些应用程序开发的试点研究的背景下，突出的优势和重要性的协同设计方法，并指出有前途的领域，为未来的研究。
We introduce the Sentinel platform that supports semantic enrichment of streamed social media data for the purposes of situational understanding. The platform is the result of a codesign effort between computing and social scientists, iteratively developed through a series of pilot studies. The platform is founded upon a knowledge-based approach, in which input streams (channels) are characterized by spatial and terminological parameters, collected media is preprocessed to identify significant terms (signals), and data are tagged (framed) in relation to an ontology. Interpretation of processed media is framed in terms of the 5W framework (who, what, when, where, and why). The platform is designed to be open to the incorporation of new processing modules, building on the knowledge-based elements (channels, signals, and framing ontology) and accessible via a set of user-facing apps. We present the conceptual architecture for the platform, discuss the design and implementation challenges of the underlying stream-processing system, and present a number of apps developed in the context of the pilot studies, highlighting the strengths and importance of the codesign approach and indicating promising areas for future research.