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

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

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Article ID: iaor201522567
Volume: 31
Issue: 5
Start Page Number: 448
End Page Number: 456
Publication Date: Nov 2014
Journal: Expert Systems
Authors: ,
Keywords: networks, knowledge management, social, medicine
Abstract:

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.

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