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Case-based reasoning and its implications for legal expert systems

Case-based reasoning and its implications for legal expert systems Reasoners compare problems to prior cases to draw conclusions about a problem and guide decision making. All Case-Based Reasoning (CBR) employs some methods for generalizing from cases to support indexing and relevance assessment and evidences two basic inference methods: constraining search by tracing a solution from a past case or evaluating a case by comparing it to past cases. Across domains and tasks, however, humans reason with cases in subtly different ways evidencing different mixes of and mechanisms for these components. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Artificial Intelligence and Law Springer Journals

Case-based reasoning and its implications for legal expert systems

Artificial Intelligence and Law , Volume 1 (3) – May 13, 2004

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Publisher
Springer Journals
Copyright
Copyright
Subject
Computer Science; Artificial Intelligence; IT Law, Media Law, Intellectual Property; Philosophy of Law; Legal Aspects of Computing; Information Storage and Retrieval
ISSN
0924-8463
eISSN
1572-8382
DOI
10.1007/BF00114920
Publisher site
See Article on Publisher Site

Abstract

Reasoners compare problems to prior cases to draw conclusions about a problem and guide decision making. All Case-Based Reasoning (CBR) employs some methods for generalizing from cases to support indexing and relevance assessment and evidences two basic inference methods: constraining search by tracing a solution from a past case or evaluating a case by comparing it to past cases. Across domains and tasks, however, humans reason with cases in subtly different ways evidencing different mixes of and mechanisms for these components.

Journal

Artificial Intelligence and LawSpringer Journals

Published: May 13, 2004

References