Title :
Closing the loop: an agenda- and justification-based framework for selecting the next discovery task to perform
Author :
Livingston, Gary R. ; Rosenberg, John M. ; Buchanan, Bruce G.
Author_Institution :
Pittsburgh Univ., PA, USA
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
Keywords :
biology computing; data mining; health care; inference mechanisms; learning (artificial intelligence); macromolecules; patient care; user interfaces; very large databases; HAMB; agenda-based framework; autonomous machine learning; background knowledge; discovery systems; general discovery strategies; justification-based architecture; justification-based framework; knowledge discovery in databases; next discovery task selection; patient rehabilitation; protein crystallization; prototype discovery program; user interests; Crystallization; Databases; Encoding; Erbium; Humans; Learning systems; Machine learning; Performance evaluation; Proteins; Prototypes;
Conference_Titel :
Data Mining, 2001. ICDM 2001, Proceedings IEEE International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
0-7695-1119-8
DOI :
10.1109/ICDM.2001.989543