Case Acquisition from Text: Ontology-based Information Extraction with SCOOBIE for myCBR

Thomas Roth-Berghofer; Benjamin Adrian; Andreas Dengel
In: Isabelle Bichindaritz; Stefania Montani (Hrsg.). Case-Based Reasoning Research and Development: 18th International Conference on Case-Based Reasoning. International Conference on Case-Based Reasoning (ICCBR-2010), 18th, July 19-22, Alessandria, Italy, Pages 451-464, Lecture Notes in Artificial Intelligence (LNAI), Vol. 6176, ISBN 978-3-642-14273-4, Springer Verlag, Heidelberg, 7/2010.


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.



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