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{
    "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/"
        }
    ]
}