Case-Based Reasoning: A Research Paradigm

By Stephen Slade. 1991

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Been Kim
2. Cynthia Rudin
3. Julie Arnold Shah
4. Elena L. Glassman
5. Giulia Vilone
6. Nadia Burkart
7. Brittney Johnson
8. Tong Wang

Citations in the corpus

• The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification (2014, background): “Studies of human decision-making and cognition provided the key inspiration for artificial intelligence Case-Based Reasoning (CBR) approaches [2, 28].”
• Interactive and interpretable machine learning models for human machine collaboration (2015, methodology): “iBCM combines CBR approaches [2, 122] with a Bayesian generative model to both generate effective clustering and provide an intuitive medium for interaction.”
• iBCM: Interactive Bayesian Case Model Empowering Humans via Intuitive Interaction (2015, methodology): “iBCM combines Case-Based Reasoning (CBR) approaches [1, 29] with a Bayesian generative model to both generate effective clustering and provide an intuitive medium for interaction.”