{"pk":31293,"title":"Representing Cases as Knowledge Sources that Apply Local Similarity Metrics","subtitle":null,"abstract":"A model of case-based reasoning is presented that relies on a procedural representation for cases. In an implementation of this model, cases are represented as knowledge sources in a blackboard architecture. Case knowledge sources define local neighborhoods of similarity and are triggered if a problem case falls within a neighborhood. This form of \"local indexing\" is a viable alternative where global similarity metrics are unavailable. Other features of this approach include the potential for fine-grained scheduling of case retrieval, a uniform representation for cases and other knowledge sources in hybrid systems that incorporate case-based reasoning and other reasoning methods, and a straightforward way to represent the actions generated by cases. This model of case-based reasoning has been implemented in a prototype system (\"Broadway\") that selects from a case base automobiles that meet a car buyer's requirements most closely and explains its selections.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Talks","is_remote":true,"remote_url":"https://escholarship.org/uc/item/7mp069vf","frozenauthors":[{"first_name":"David","middle_name":"B.","last_name":"Skalak","name_suffix":"","institution":"University of Massachusetts","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"1992-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/31293/galley/22362/download/"}]}