Noise-free attribute-oriented induction

Attribute-oriented induction (AOI) was originally developed to facilitate the mining of generalized knowledge in relational databases. Input data for the AOI method comprises a relational table and a concept tree for each attribute. The output is a small relation that contains a number of generalized tuples which summarize the general characteristics of the relational table. Ideally, the generalized tuples shown in the induction table represent the patterns of information that appear in the table. However, if the input data contains a large amount of noise, the generalized tuples may contain too little information to be useful. Existing research into AOI has yet to focus on the elimination of noise. To fill this gap, we developed two noise-free AOI algorithms that filter out noise to enhance the specificity of AOI results. (c) 2021 Elsevier Inc. All rights reserved.

Automated summary

Attribute-oriented induction (AOI) is a method developed for mining generalized knowledge in relational databases by summarizing input data into a small relation containing generalized tuples. Existing research has not yet focused on noise elimination, but to address this gap, two noise-free AOI algorithms have been developed to enhance result specificity.