A Textual Case-Based Reasoning Framework for Knowledge Management Applications

Department of Computer Science, University of Maryland, College Park, MD 20742 -3255lastname@aic.nrl.navy.mil Abstract . Knowledge management (KM) systems manipulate organizational knowledge by storing and redistributing corporate memories that are acquired from the organization’s members. In this paper, we introduce a textual case-based reasoning (TCBR) framework for KM systems that manipulates organizational knowledge embedded in artifacts (e.g., best practices, alerts, lessons learned). The TCBR approach acquires knowledge from human users (via knowledge elicitation) and from text documents (via knowledge extraction) usi ng template-based information extraction methods, a subset of natural language, and a domain ontology. Organizational knowledge is stored in a case base and is distributed in the context of targeted processes (i.e., within external distribution systems). The knowledge artifacts in the case base have to be translated into the format of the external distribution systems. A domain ontology supports knowledge elicitation and extraction, storage of knowledge artifacts in a case base, and artifact translation.

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