Titlebook: Case-Based Reasoning Research and Development; 28th International C Ian Watson,Rosina Weber Conference proceedings 2020 Springer Nature Swi

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A User-Centric Evaluation to Generate Case-Based Explanations Using Formal Concept Analysisation, act as a black box for users. Explanations for recommender systems are useful to make recommendations more effective and help the users to trust the system and understand why certain items have been recommended. In this paper, we propose a post-hoc model-agnostic explanation system for MF rec

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https://doi.org/10.1007/978-1-4684-0754-9to compare running and completed workflow instances. We implemented and evaluated our approach in the ProCAKE framework. The proposed similarity measure achieves promising results considering runtime and similarity assessment.

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Organotransition-Metal Chemistryommendations based on Case-Based Reasoning and Formal Concept Analysis. We have conducted an experimental evaluation with real users to define what are the most useful explanation features that allow users a better understanding of the system recommendation.

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