Noise-free attribute-oriented induction

Hsiao Wei Hu, Yen Liang Chen, Jia Yu Hong

研究成果: 雜誌貢獻期刊論文同行評審

1 引文 斯高帕斯(Scopus)


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.

頁(從 - 到)333-349
期刊Information Sciences
出版狀態已出版 - 8月 2021


深入研究「Noise-free attribute-oriented induction」主題。共同形成了獨特的指紋。