A Framework to Evaluate the Quality of Integrated Datasets-Reference-Cited by-同舟云学术

A Framework to Evaluate the Quality of Integrated Datasets

Published:2022-12 Issue:4 Volume:22 Page:5-23
ISSN:1559-6915
Container-title:ACM SIGAPP Applied Computing Review
language:en
Short-container-title:SIGAPP Appl. Comput. Rev.

Author:

Buono Francesco Del¹,Faggioli Guglielmo²,Paganelli Matteo¹,Baraldi Andrea¹,Guerra Francesco¹,Ferro Nicola²

Affiliation:

1. University of Modena and Reggio Emilia, Modena, Italy

2. University of Padua, Padua, Italy

Abstract

Evaluation is a bottleneck in data integration processes: it is performed by domain experts through manual onerous data inspections. This task is particularly heavy in real business scenarios, where the large amount of data makes checking all integrated tuples infeasible. Our idea is to address this issue by providing the experts with an unsupervised measure, based on word frequencies, which quantifies how much a dataset is representative of another dataset, giving an indication of how good is the integration process. The paper motivates and introduces the measure and provides extensive experimental evaluations, that show the effectiveness and the efficiency of the approach.

Publisher

Association for Computing Machinery (ACM)

Subject

Industrial and Manufacturing Engineering

Link

https://dl.acm.org/doi/pdf/10.1145/3584014.3584015

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