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Extracting knowledge from web communities and linked data for case‐based reasoning systems
Author(s) -
Sauer Christian Severin,
RothBerghofer Thomas
Publication year - 2014
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/exsy.12034
Subject(s) - computer science , workbench , task (project management) , linked data , process (computing) , semantic web , knowledge extraction , data web , world wide web , data science , information retrieval , data mining , web service , management , economics , visualization , operating system
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.