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Extracting knowledge from web communities and linked data for case-based reasoning systems

机译:从Web社区中提取知识,并为基于案例的推理系统提供链接数据

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摘要

Web communities and the Web 2.0 provide a huge amount of experiences and there has been a growing availability of Linked Open Data. Making experiences and data available as knowledge to be used in case-based reasoning CBR systems is a current research effort. The process of extracting such knowledge from the diverse data types used in web communities, to transform data obtained from Linked Data sources, and then formalising it for CBR, is not an easy task. In this paper, we present a prototype, the Knowledge Extraction Workbench KEWo, which supports the knowledge engineer in this task. We integrated the KEWo into the open-source case-based reasoning tool myCBR Workbench. We provide details on the abilities of the KEWo to extract vocabularies from Linked Data sources and generate taxonomies from Linked Data as well as from web community data in the form of semi-structured texts.
机译:Web社区和Web 2.0提供了大量的经验,并且链接开放数据的可用性也在不断增长。当前的研究工作是将经验和数据作为知识用于基于案例的推理CBR系统。从网络社区中使用的各种数据类型中提取此类知识,转换从链接数据源获得的数据,然后将其形式化以进行CBR的过程并非易事。在本文中,我们提出了一个原型,即知识提取工作台KEWo,它为知识工程师提供了支持。我们将KEWo集成到基于案例的开源推理工具myCBR Workbench中。我们详细介绍了KEWo从链接数据源中提取词汇表,从链接数据以及网络社区数据中以半结构化文本形式生成分类法的能力。

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