In this paper, we introduce IBP, an algorithm that combines g with an abstract domain model and case-based reasoning techniques to predict the outcome of case-based legal argument...
Multi-case-base reasoning (MCBR) extends case-based reasoning to draw on multiple case bases that may address somewhat different tasks. In MCBR, an agent selectively supplements i...
This paper is an empirical investigation into the effectiveness of linear scaling adaptation for case-based software project effort prediction. We compare two variants of a linea...
Colin Kirsopp, Emilia Mendes, Rahul Premraj, Marti...
How to endow case-based reasoning systems with effective case adaptation capabilities is a classic problem. A significant impediment to developing automated adaptation procedures i...
We propose a new approach for learning Bayesian classifiers from data. Although it relies on traditional Bayesian network (BN) learning algorithms, the effectiveness of our approa...