Taxonomic Semantic Indexing for Textual Case-Based Reasoning

Abstract. Case-Based Reasoning (CBR) solves problems by reusing past problemsolving experiences maintained in a casebase. The key CBR knowledge container therefore is its casebase. However there are further containers such as similarity, reuse and revision knowledge that are also crucial. Automated acquisition approaches are particularly attractive to discover knowledge for such containers. Majority of research in this area is focused on introspective algorithms to extract knowledge from within the casebase. However the rapid increase in Web applications has resulted in large volumes of user generated experiential content. This forms a valuable source of background knowledge for CBR system development. In this paper we present a novel approach to acquiring knowledge from Web pages. The primary knowledge structure is a dynamically generated taxonomy which once created can be used during the retrieve and reuse stages of the CBR cycle. Importantly this taxonomy is pruned according to a cl...

• Type: Journal
• Year: 2010
• Where: ICCBR
• Authors: Juan A. Recio-García, Nirmalie Wiratunga
• Keywords: Automated Reasoning, CBR Knowledge Container, ICCBR 2010, Primary Knowledge Structure, Sense Disambiguation