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Knowledge integration of distributed enterprises using cloud based big data analytics

机译：使用基于云的大数据分析进行分布式企业的知识整合

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An efficient and adaptive centralization of disparate knowledge sources is a key factor for the success of knowledge management systems (KMS) in distributed heterogeneous enterprises such as healthcare and production systems with large scale and disparate knowledge sources. Professional end users of such systems (e.g. physicians and production engineers) should have nearly real-time access to the records to provide relevant decisions without any difficulty of dealing with IT systems. Analysis and reasoning of professional end users' feedback lead helpful knowledge bases which can be used for future decision making situations such as diagnostics and predictions. This paper represents an overview of the cloud computing based conceptual framework for the integration of distributed knowledge sources in large scale heterogeneous enterprises such as grouped hospitals, clinic chains, production systems, supply chains and etc. The NoSQL database is used for providing a scalable data analytics. This framework facilitates accessible, efficient and always available knowledge bases for collaborative systems and reduces redundancy and costs by sharing the knowledge between individuals and experts. Three different application scenarios will be used to test and evaluate the efficiency of the proposed framework. Distributed product design and development, healthcare knowledge integration and providing readability in drug leaflets are target application domains of this research.
机译：高效且自适应地对各种知识源进行集中管理是知识型管理系统（KMS）在分布式异构企业（例如具有大规模和不同知识源的医疗保健和生产系统）中取得成功的关键因素。此类系统的专业最终用户（例如医生和生产工程师）应几乎实时访问记录，以提供相关决策，而不会遇到与IT系统打交道的任何困难。专业最终用户反馈的分析和推理可提供有用的知识库，这些知识库可用于将来的决策情况，例如诊断和预测。本文代表了基于云计算的概念框架的概述，该概念框架用于在大型异构企业（如组合医院，诊所链，生产系统，供应链等）中集成分布式知识源。NoSQL数据库用于提供可扩展的数据分析。该框架促进了协作系统的可访问，高效且始终可用的知识库，并通过在个人和专家之间共享知识来减少冗余和成本。三种不同的应用场景将用于测试和评估所提出框架的效率。分布式产品设计和开发，医疗保健知识集成以及在药物说明书中提供可读性是本研究的目标应用领域。

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