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

Sauer, Christian and Roth-Berghofer, Thomas (2014) Extracting knowledge from web communities and linked data for case-based reasoning systems. Expert Systems, 31 (5). pp. 448-456. ISSN 0266-4720

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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.

Item Type: Article
Additional Information: © 2013 Wiley Publishing Ltd. This is the accepted version of the following article: Sauer C. S., and Roth-Berghofer T. (2014), Extracting knowledge from web communities and linked data for case-based reasoning systems, Expert Systems, 31, pages 448–456, which has been published in final form at https://doi.org/10.1111/exsy.12034.
Uncontrolled Keywords: information extraction; case-based reasoning; experience web; linked data
Subjects: Computing
Depositing User: Christian Sauer
Date Deposited: 17 Dec 2013 15:36
Last Modified: 09 May 2017 10:01
URI: http://repository.uwl.ac.uk/id/eprint/522

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