Paper Info
Title
A study on the modified attribute oriented induction algorithm of mining the multi-value attribute data
Abstract
Attribute Oriented Induction method (short for AOI) is one of the most important methods of data mining. The input value of AOI contains a relational data table and attribute-related concept hierarchies. The output is a general feature inducted by the related data. Though it is useful in searching for general feature with traditional AOI method, it only can mine the feature from the single-value attribute data. If the data is of multiple-value attribute, the traditional AOI method is not able to find general knowledge from the data. In addition, the AOI algorithm is based on the way of induction to establish the concept hierarchies. Different principles of classification or different category values produce different concept trees, therefore, affecting the inductive conclusion. Based on the issue, this paper proposes a modified AOI algorithm combined with a simplified Boolean bit Karnaugh map. It does not need to establish the concept tree. It can handle data of multi value and find out the general features implied within the attributes.
Year
DOI
Venue
2012
10.1007/978-3-642-28487-8_36
ACIIDS (1)
Keywords
Field
DocType
modified attribute,concept hierarchy,single-value attribute data,data mining,attribute-related concept hierarchy,multi-value attribute data,induction algorithm,modified aoi algorithm,related data,relational data table,aoi algorithm,traditional aoi method,general feature,karnaugh map
Data mining,Relational database,Computer science,Attribute oriented induction,Variable and attribute,Algorithm,Karnaugh map,General knowledge,Artificial intelligence,Hierarchy,Machine learning,Attribute domain
Conference
Volume
ISSN
Citations 
7196
0302-9743
0
PageRank 
References 
Authors
0.34
12
3
Name
Order
Citations
PageRank
Shu-Meng Huang101.35
Ping-Yu Hsu227641.77
Wan-Chih Wang3120.98