Ordinal Association Rules for Error Identification in Data Sets

A new extension of the Boolean association rules, ordinal association rules, that incorporates ordinal relationships among data items, is introduced. One use for ordinal rules is to identify possible errors in data. A method that finds these rules and identifies potential errors in data is proposed. Keywords Data Mining, Data Cleansing, Association Rules, Ordinal Rules.

• Type: Conference
• Year: 2001
• Where: CIKM
• Authors: Andrian Marcus, Jonathan I. Maletic, King-Ip Lin
• Keywords: Association Rules, Boolean Association Rules, CIKM 2001, Information Management, Ordinal Rules