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Combined association rules for dealing with missing values

Department of Management Information Systems,National Chung Hsing University, Taichung, Taiwan, R.O.C.

Chin-Chen Chang

Department of Information Engineering and Computer Science, Feng Chia University, Taichung, Taiwan, R.O.C., Department of Computer Science and Information Engineering, National Chung Cheng University, ChiaYi, Taiwan, R.O.C., ccc{at}cs.ccu.edu.tw

Yu-Chiang Li

Department of Computer Science and Information Engineering, National Chung Cheng University, ChiaYi, Taiwan, R.O.C.

With the rapid increase in the use of databases, the problem of missing values inevitably arises. The techniques developed to recover these missing values effectively should be highly precise in order to estimate the missing values completely. The mining of association rules can effectively establish the relationship among items in databases. Therefore, discovered association rules are usually applied to recover the missing values in databases. This study presents a Fast Recycle Combined Association Rules (FRCAR) method to fill in the missing values. FRCAR applies a technique to recycle sub-frequent itemsets and bit-arrays to discover more association rules than the Missing Value Completion (MVC) approach. The experimental result demonstrates that FRCAR results in a higher recovery rate and higher recovery accuracy for missing values.

Key Words: association rule • data mining • missing value • relational database

This version was published on August 1, 2007

Journal of Information Science, Vol. 33, No. 4, 468-480 (2007)
DOI: 10.1177/0165551506075329


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