An AI Planning System for Data Cleaning

被引：4

作者：

Boselli, Roberto ^{[1
,2
]}

Cesarini, Mirko ^{[1
,2
]}

Mercorio, Fabio ^{[1
,2
]}

Mezzanzanica, Mario ^{[1
,2
]}

机构：

[1] Univ Milano Bicocca, Dept Stat & Quantitat Methods, Milan, Italy

[2] Univ Milano Bicocca, CRISP Res Ctr, Milan, Italy

来源：

MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2017, PT III | 2017年 / 10536卷

关键词：

AI planning; Data quality; Data cleaning; ETL; CHECKING;

D O I：

10.1007/978-3-319-71273-4_29

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Data Cleaning represents a crucial and error prone activity in KDD that might have unpredictable effects on data analytics, affecting the believability of the whole KDD process. In this paper we describe how a bridge between AI Planning and Data Quality communities has been made, by expressing both the data quality and cleaning tasks in terms of AI planning. We also report a real-life application of our approach.

引用

页码：349 / 353

页数：5