What's new? Using prior models as a measure of novelty in knowledge discovery

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12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'00)

Vancouver, British Columbia, Canada

November 13-November 15

ISBN: 0-7695-0909-6

	ASCII Text	x
	J. Ludwig, G. Livingston, E. Vozalis, B. Buchanan, "What's new? Using prior models as a measure of novelty in knowledge discovery," Tools with Artificial Intelligence, IEEE International Conference on, pp. 0086, 12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'00), 2000.

	BibTex	x
	@article{ 10.1109/TAI.2000.889850, author = {J. Ludwig and G. Livingston and E. Vozalis and B. Buchanan}, title = {What's new? Using prior models as a measure of novelty in knowledge discovery}, journal ={Tools with Artificial Intelligence, IEEE International Conference on}, volume = {0}, year = {2000}, isbn = {0-7695-0909-6}, pages = {0086}, doi = {http://doi.ieeecomputersociety.org/10.1109/TAI.2000.889850}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Tools with Artificial Intelligence, IEEE International Conference on TI - What's new? Using prior models as a measure of novelty in knowledge discovery SN - 0-7695-0909-6 SP EP A1 - J. Ludwig, A1 - G. Livingston, A1 - E. Vozalis, A1 - B. Buchanan, PY - 2000 KW - data mining; very large databases; medical information systems; prior models; knowledge discovery; novelty; background knowledge; pneumonia outcome data; large databases; medical database VL - 0 JA - Tools with Artificial Intelligence, IEEE International Conference on ER -

J. Ludwig, Dept. of Comput. Sci., Pittsburgh Univ., PA, USA

G. Livingston, Dept. of Comput. Sci., Pittsburgh Univ., PA, USA

E. Vozalis, Dept. of Comput. Sci., Pittsburgh Univ., PA, USA

B. Buchanan, Dept. of Comput. Sci., Pittsburgh Univ., PA, USA

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TAI.2000.889850

Abstract: One of the challenges of knowledge discovery is identifying patterns that are interesting, with novelty an important component of interestingness. Another important aspect of knowledge discovery is making efficient use of background knowledge. This paper develops a definition of novelty relative to a prior model of the domain. The definition of novelty is tested using pneumonia outcome data and a prior model of pneumonia severity.

Index Terms:

data mining; very large databases; medical information systems; prior models; knowledge discovery; novelty; background knowledge; pneumonia outcome data; large databases; medical database

Citation:

J. Ludwig, G. Livingston, E. Vozalis, B. Buchanan, "What's new? Using prior models as a measure of novelty in knowledge discovery," ictai, pp.0086, 12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'00), 2000

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