One of the motivations for research in data quality is to automatically identify cleansing activities, namely a sequence of actions able to cleanse a dirty dataset, which today are often developed manually by domain-experts. Here we explore the idea that AI Planning can contribute to identify data inconsistencies and automatically fix them. To this end, we formalise the concept of cost-optimal Universal Cleanser — a collection of cleansing actions for each data inconsistency — as a planning problem. We present then a motivating government application in which it has be used

Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M. (2014). Planning meets Data Cleansing. In Proceedings of The 24th International Conference on Automated Planning and Scheduling (ICAPS) (pp.439-443).

Planning meets Data Cleansing

BOSELLI, ROBERTO;CESARINI, MIRKO;MERCORIO, FABIO;MEZZANZANICA, MARIO
2014

Abstract

One of the motivations for research in data quality is to automatically identify cleansing activities, namely a sequence of actions able to cleanse a dirty dataset, which today are often developed manually by domain-experts. Here we explore the idea that AI Planning can contribute to identify data inconsistencies and automatically fix them. To this end, we formalise the concept of cost-optimal Universal Cleanser — a collection of cleansing actions for each data inconsistency — as a planning problem. We present then a motivating government application in which it has be used
paper
Data quality; data cleansing; government application
English
The International Conference on Automated Planning and Scheduling (ICAPS) - June 21-26
2014
Proceedings of The 24th International Conference on Automated Planning and Scheduling (ICAPS)
978-1-57735-660-8
2014
2014-January
January
439
443
http://www.aaai.org/ocs/index.php/ICAPS/ICAPS14/paper/view/7898
none
Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M. (2014). Planning meets Data Cleansing. In Proceedings of The 24th International Conference on Automated Planning and Scheduling (ICAPS) (pp.439-443).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/52130
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