학술논문

Closing the loop: an agenda- and justification-based framework for selecting the next discovery task to perform
Document Type
Conference
Source
Proceedings 2001 IEEE International Conference on Data Mining Data mining Data Mining, 2001. ICDM 2001, Proceedings IEEE International Conference on. :385-392 2001
Subject
Computing and Processing
Performance evaluation
Encoding
Prototypes
Proteins
Crystallization
Machine learning
Databases
Learning systems
Humans
Erbium
Language
Abstract
We propose and evaluate an agenda- and justification-based architecture for discovery systems that selects the next tasks to perform. This framework has many desirable properties: (1) it facilitates the encoding of general discovery strategies using a variety of background knowledge, (2) it reasons about the appropriateness of the tasks being considered, and (3) it tailors its behavior toward a user's interests. A prototype discovery program called HAMB demonstrates that both reasons and estimates of interestingness contribute to performance in the domains of protein crystallization and patient rehabilitation.