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Semantic Scout: Making Sense of Organizational Knowledge

机译:语义侦察员:了解组织知识

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Knowledge takes many forms in large organizations, and a unique opportunity exists to perform substantial integration of heterogeneous knowledge through semantic technologies. We present a sustainable method to create and maintain a data cloud that provides added value to an organization, while not interfering with existing practices. Our method shows one of the first application of knowledge-centric data access, following a web 3.0 paradigm. A use case has been implemented in a large research organization, based on explicit requirements. RDF-OWL datasets generated on the basis of a highly modular, patternbased ontology are created, enriched by means of inferences and NLP techniques, and are integrated with linked open data. They are presented in different interaction modes that embrace important tasks such as navigation and search of organizational knowledge from any point, expert finding, competence matching etc. The tools implemented have been submitted to end-users for a task-based evaluation.
机译:在大型组织中,知识采取多种形式,并且存在通过语义技术执行异构知识的大量集成的独特机会。我们提供一种可持续的方法来创建和维护数据云,该数据云可为组织提供增值,同时又不干扰现有实践。我们的方法遵循Web 3.0范例,展示了以知识为中心的数据访问的第一个应用程序。根据明确的要求,已经在大型研究组织中实现了用例。创建基于高度模块化,基于模式的本体的RDF-OWL数据集,并通过推理和NLP技术加以丰富,并与链接的开放数据集成。它们以不同的交互模式呈现,包含重要任务,例如从任何角度导航和搜索组织知识,专家发现,能力匹配等。所实施的工具已提交给最终用户以基于任务的评估。

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