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

  • Thomas Roth-Berghofer
  • Benjamin Adrian
  • Andreas Dengel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6176)

Abstract

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.

Keywords

Textual Case-Based Reasoning Ontology-based Information Extraction Linked Open Data Web of Data 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Thomas Roth-Berghofer
    • 1
    • 2
  • Benjamin Adrian
    • 1
    • 2
  • Andreas Dengel
    • 1
    • 2
  1. 1.Knowledge Management DepartmentGerman Research Center for Artificial Intelligence (DFKI) GmbHKaiserslauternGermany
  2. 2.Knowledge-Based Systems Group, Department of Computer ScienceUniversity of KaiserslauternKaiserslautern

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