(Enter summary)
Abstract: Knowledge discovery in databases, or data mining,
is an important issue in the development of data- and
knowledge-base systems. An attribute-oriented induction
method has been developed for knowledge discovery in
databases. The method integrates a machine learning
paradigm, especially learning-from-examples techniques,
with set-oriented database operations and extracts generalized
data from actual data in databases. An
attribute-oriented concept tree ascension technique is
applied in... (Update)
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BibTeX entry: (Update)
J. Han, Y. Cai, and N. Cercone. Knowledge discovery in databases: An attribute-oriented approach. In Proc. 18th Int. Conf. Very Large Data Bases, pages 547--559, Vancouver, Canada, August 1992. http://citeseer.ist.psu.edu/han92knowledge.html More
@inproceedings{ han92knowledge,
author = "Jiawei {Han} and Yandong {Cai} and Nick {Cercone}",
title = "Knowledge Discovery in Databases: An Attribute-Oriented Approach",
booktitle = "Proceedings of the 18th International Conference on Very Large Databases",
publisher = "Morgan Kaufmann Publishers",
address = "San Francisco, U.S.A.",
editor = "Li-Yan {Yuan}",
isbn = "1-55860-151-1",
pages = "547--559",
year = "1992",
url = "citeseer.ist.psu.edu/han92knowledge.html" }
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