Knowledge Extraction and Summarization for an Application of Textual Case-Based Interpretation

Authors:
Eni Mustafaraj;Martin Hoof;Bernd Freisleben
Affiliations:
Dept. of Mathematics and Computer Science, University of Marburg,;Dept. of Electrical Engineering, Fachhochschule Kaiserslautern,;Dept. of Mathematics and Computer Science, University of Marburg,
Venue:
ICCBR '07 Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Year:
2007

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Abstract

This paper presents KES (Knowledge Extraction and Summarization), a new knowledge-enhanced approach that builds a case memory out of episodic textual narratives. These narratives are considered as generated probabilistically by the structure of the task they describe. The task elements are then used to construct the structure of the case memory. The KES approach is illustrated with examples and an empirical evaluation of a real-world scenario of textual case-based interpretation for a technical domain.