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.
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Mustafaraj, E., Hoof, M., Freisleben, B. (2007). Knowledge Extraction and Summarization for an Application of Textual Case-Based Interpretation. In: Weber, R.O., Richter, M.M. (eds) Case-Based Reasoning Research and Development. ICCBR 2007. Lecture Notes in Computer Science(), vol 4626. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74141-1_36
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DOI: https://doi.org/10.1007/978-3-540-74141-1_36
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