Case acquisition from text: ontology-based information extraction with SCOOBIE for myCBR

Roth-Berghofer, Thomas, Adrian, Benjamin and Dengel, Andreas (2010) Case acquisition from text: ontology-based information extraction with SCOOBIE for myCBR. In: Case-Based Reasoning. Research and Development. Lecture Notes in Computer Science, 6176. Springer, Heidelberg, Germany, pp. 451-464. ISBN 9783642142734

[thumbnail of Case-acquisition-from-text.pdf]
Case-acquisition-from-text.pdf - Accepted Version

Download (796kB) | Preview


myCBR is a freely available tool for rapid prototyping of similarity-based retrieval applications such as case-based product recommender systems. It provides easy-to-use model generation, data import, similarity modelling, explanation, and testing functionality together with comfortable graphical user interfaces. SCOOBIE is an ontology-based information extraction system, which uses symbolic background knowledge for extracting information from text. Extraction results depend on existing knowledge fragments. In this paper we show how to use SCOOBIE for generating cases from texts. More concrete we use ontologies of the Web of Data, published as so called Linked Data interlinked with myCBR’s case model. We present a way of formalising a case model as Linked Data ready ontology and connect it with other ontologies of the Web of Data in order to get richer cases.

Item Type: Book Section
Identifier: 10.1007/978-3-642-14274-1_33
Additional Information: © Springer Verlag 2010. The final publication is available at Springer via
Keywords: Textual Case-Based Reasoning, Ontology-based Information Extraction, Linked Open Data, Web of Data
Subjects: Computing
Depositing User: Rod Pow
Date Deposited: 17 Sep 2014 11:19
Last Modified: 28 Aug 2021 07:05


Downloads per month over past year

Actions (login required)

View Item View Item