This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
senting them at different levels of abstraction. This can make the analysis complex and unwieldy, requiring teams of analysts to manage it. A new approach to managing the complexit...
Much information and knowledge work (with and without information technology) can be characterised as multitasking and interrupt driven. A whole host of characterisations and buzz...
We propose in this paper a general framework for integrating inductive and case-based reasoning (CBR) techniques for diagnosis tasks. We present a set of practical integrated appro...
Eric Auriol, Michel Manago, Klaus-Dieter Althoff, ...
Maps are artifacts often derived from multiple sources of data, e.g., sensors, and processed by multiple methods, e.g., gridding and smoothing algorithms. As a result, complex meta...
Nicholas Del Rio, Paulo Pinheiro da Silva, Ann Q. ...