Probabilistic Approach to Association Rules in Incomplete Databases

Authors:
Marzena Kryszkiewicz
Affiliations:
-
Venue:
WAIM '00 Proceedings of the First International Conference on Web-Age Information Management
Year:
2000

Citing 2
Cited 2

Mining association rules between sets of items in large databases

SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Treatment of Missing Values for Association Rules

PAKDD '98 Proceedings of the Second Pacific-Asia Conference on Research and Development in Knowledge Discovery and Data Mining

Legitimate Approach to Association Rules under Incompleteness

ISMIS '00 Proceedings of the 12th International Symposium on Foundations of Intelligent Systems
Mining rules from an incomplete dataset with a high missing rate

Expert Systems with Applications: An International Journal

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Abstract

In the paper we list a set of properties that characterize a legitimate approach to data incompleteness. An example of a legitimate probabilistic approach, which is based on attribute distribution, is presented. We also review and compare three other approaches to incompleteness: the one that ignores missing values, the approach applying only certain information, and the approach based on valid databases. All the three approaches turn out to be invalid.