Extending CBR with Multiple Knowledge Sources from Web

Recio-Garcí­a, Juan A.; Casado-Hernández, Miguel A.; Dí­az-Agudo, Belén

doi:10.1007/978-3-642-14274-1_22

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…Recio‐García et al . ()). An issue yet to be solved is the already‐mentioned problem of numerous possible combinations of source data and targeted knowledge container(s) for which knowledge is to be extracted.…”

Section: Related Workmentioning

confidence: 94%

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

Sauer

Roth–Berghofer

2013

Expert Systems

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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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Section: Related Workmentioning

confidence: 94%

“…As Recio‐García et al . point out, there are a variety of opportunities if web‐based data sources can be integrated into a development framework for CBR systems such as jCOLIBRI (Recio‐García et al ., ). Their approach is similar to the approach described in this paper.…”

Section: Related Workmentioning

confidence: 97%

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

Sauer

Roth–Berghofer

2013

Expert Systems

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“…Next, the disaggregation of the CBR methodology into services is explained. The four main phases of the CBR cycle (Recio- García et al, 2010) are divided into different services covering the entrance of data, the recovery of information from the case base and the solution generation and validation. The data used to check the OBIFS system were a subset of the available data that had not been previously used in the training phase.…”

Section: System Descriptionmentioning

confidence: 99%

(OBIFS) isotropic image analysis for improving a predicting agent based systems

Muñoz

Mata

Corchado

et al. 2013

Expert Systems with Applications

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In this interdisciplinary study a novel hybrid forecasting system is presented, in which an isotropic buffer operator is applied for case-based creation within the structure of the organization-based multi-agent system. Commonly used as an image analysis technique by commercial Geographic Information Systems (GIS), the buffer operator in this particular system calculates the area of a forest fire for prediction and visualization tasks. The use of the buffer operator improves the quality of the data used by the system and in consequence the quality of the results obtained. The system has been successfully tested using real historical data on forest fires evolution, by generating accurate predictions.

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Web Community Knowledge Extraction for myCBR 3

Sauer

Roth–Berghofer

2011

Research and Development in Intelligent Systems XXVIII

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Extending CBR with Multiple Knowledge Sources from Web

Cited by 4 publications

References 12 publications

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

(OBIFS) isotropic image analysis for improving a predicting agent based systems

Web Community Knowledge Extraction for myCBR 3

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