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
收藏
页码：349 / 353
页数：5
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