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Value-oriented Big Data processing with applications

机译:面向价值的大数据处理与应用程序

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We discuss the nature of Big Data and address the role of semantics in analyzing and processing Big Data that arises in the context of Physical-Cyber-Social Systems. To handle Volume, we advocate semantic perception that can convert low-level observational data to higher-level abstractions more suitable for decision-making. To handle Variety, we resort to semantic models and annotations of data so that intelligent processing can be done independent of heterogeneity of data formats and media. To handle Velocity, we seek to use continuous semantics capability to dynamically create event or situation specific models and recognize relevant new concepts, entities and facts. To handle Veracity, we explore trust models and approaches to glean trustworthiness. Our ultimate goal is to deal with the challenges due to the four Vs of Big Data to derive Value to enable decision-making and action.
机译:我们讨论了大数据的本质,并探讨了语义在分析和处理物理网络社会系统中出现的大数据中的作用。为了处理Volume,我们提倡语义感知,该感知可以将低层观察数据转换为更适合决策的高层抽象。为了处理多样化,我们求助于语义模型和数据注释,以便可以独立于数据格式和媒体的异构性而进行智能处理。为了处理速度,我们寻求使用连续语义功能来动态创建特定于事件或情况的模型,并识别相关的新概念,实体和事实。为了处理准确性,我们探索了信任模型和方法来收集信任度。我们的最终目标是应对大数据的四个V带来的挑战,以获取价值以实现决策和行动。

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