Retrieval, reuse, revision and retention in case-based reasoning
Ramon López de Mántaras,David McSherry,Derek Bridge,David B. Leake,Barry Smyth,Susan Craw,Boi Faltings,Mary Lou Maher,Michael T. Cox,Kenneth D. Forbus,Mark T. Keane,Agnar Aamodt,Ian Watson +12 more
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TLDR
The cognitive science foundations of CBR and its relationship to analogical reasoning are examined, and a representative selection ofCBR research in the past few decades on aspects of retrieval, reuse, revision and retention are reviewed.Abstract:
Case-based reasoning (CBR) is an approach to problem solving that emphasizes the role of prior experience during future problem solving (i.e., new problems are solved by reusing and if necessary adapting the solutions to similar problems that were solved in the past). It has enjoyed considerable success in a wide variety of problem solving tasks and domains. Following a brief overview of the traditional problem-solving cycle in CBR, we examine the cognitive science foundations of CBR and its relationship to analogical reasoning. We then review a representative selection of CBR research in the past few decades on aspects of retrieval, reuse, revision and retention.read more
Citations
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Cloud-enabled prognosis for manufacturing
Robert X. Gao,Lihui Wang,Roberto Teti,David Dornfeld,Soundar R. T. Kumara,Masahiko Mori,Moneer Helu +6 more
TL;DR: The historical development of prognosis theories and techniques and their future growth enabled by the emerging cloud infrastructure are reviewed and techniques for cloud computing are highlighted.
Book ChapterDOI
Case-based recommendation
TL;DR: This chapter describes the basic approach to case-based recommendation, highlighting how it differs from other recommendation technologies, and introducing some recent advances that have led to more powerful and flexible recommender systems.
Journal ArticleDOI
The spectrum-based learner: A new local approach for modeling soil vis–NIR spectra of complex datasets
Leonardo Ramirez-Lopez,Leonardo Ramirez-Lopez,Thosten Behrens,Karsten Schmidt,Antoine Stevens,José Alexandre Melo Demattê,Thomas Scholten +6 more
TL;DR: It is shown that memory-based learning (MBL) is a very promising approach to deal with complex soil visible and near infrared (vis–NIR) datasets and that soil vis-NIR distance matrices can be used to further improve the prediction performance of spectral models.
Journal ArticleDOI
Learning adaptation knowledge to improve case-based reasoning
TL;DR: An introspective learning approach where the case knowledge itself provides a source from which training data for the adaptation task can be assembled, and an ensemble of these property-based adaptation classifiers has been particularly successful for the most difficult of the symbolic adaptation tasks in tablet formulation.
Journal ArticleDOI
Similarity assessment and efficient retrieval of semantic workflows
Ralph Bergmann,Yolanda Gil +1 more
TL;DR: A new generic model for representing workflows as semantically labeled graphs is described, together with a related model for knowledge intensive similarity measures, and a new retrieval algorithm is introduced that goes beyond traditional sequential retrieval for graphs, interweaving similarity computation with case selection.
References
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Nearest neighbor pattern classification
Thomas M. Cover,Peter E. Hart +1 more
TL;DR: The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points, so it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.
Journal ArticleDOI
Features of Similarity
TL;DR: The metric and dimensional assumptions that underlie the geometric representation of similarity are questioned on both theoretical and empirical grounds and a set of qualitative assumptions are shown to imply the contrast model, which expresses the similarity between objects as a linear combination of the measures of their common and distinctive features.
Journal ArticleDOI
Case-based reasoning: foundational issues, methodological variations, and system approaches
Agnar Aamodt,Enric Plaza +1 more
TL;DR: An overview of the foundational issues related to case-based reasoning is given, some of the leading methodological approaches within the field are described, and the current state of the field is exemplified through pointers to some systems.
Book
Case-based reasoning
TL;DR: Case-based reasoning as discussed by the authors is one of the fastest growing areas in the field of knowledge-based systems and the first comprehensive text on the subject is presented by a leader in this field.
Journal ArticleDOI
Structure‐Mapping: A Theoretical Framework for Analogy*
TL;DR: In this paper, the interpretation rules of OS implicit rules for mapping knowledge about a base domain into a torget domain are defined by the existence of higher-order relations, which depend only on syntactic properties of the knowledge representation, and not on specific content of the domoins.