Titlebook: Case-Based Reasoning Research and Development; 27th International C Kerstin Bach,Cindy Marling Conference proceedings 2019 Springer Nature

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Diffusion Pathway of Oxygen in OX Lungrevious case-based reasoning (CBR) research has developed criteria for assigning confidence to the solutions of a CBR system. This paper investigates whether such analysis, coupled with factors such as CBR system competence, can be used to predict confidence in the outputs of a black box system, whe

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https://doi.org/10.1007/978-1-4615-9692-9ating patterns. These vectors represent, somehow, a characterization of the user preferences in a lower dimensionality space. Although matrix factorization is more accurate that other recommendation strategies, the main problem associated with this approach is that the discovered factors are opaque

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Transmitted-light crystallography,winning of artificial neural networks (ANNs) with case-based reasoning (CBR) systems; so-called ANN-CBR twins. It surveys these systems to advance a new theoretical interpretation of previous work and define a road map for CBR’s further role in XAI. A systematic survey of 1,102 papers was conducted

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Oxygen Free Radicals and Tissue Injury,ulture, by improving resource-utilization through better on-farm, management decisions. However, smart agriculture’s promise is often challenged by the high barriers to user adoption. This paper develops a case-based reasoning (CBR) system called PBI-CBR to predict grass growth for dairy farmers, th

Militia

https://doi.org/10.1007/978-1-4615-9840-4putationally expensive similarity assessment. The two-phase MAC/FAC (“Many are called, but few are chosen”) retrieval has been proven useful to reduce the retrieval time but comes at the cost of an additional modeling effort for implementing the MAC phase. In this paper, we present a new approach to

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