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Ordinal assessment of data consistency based on regular expressions

Antoon Bronselaer (UGent) , Joachim Nielandt (UGent) , Robin De Mol (UGent) and Guy De Tré (UGent)
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Abstract
In this paper, a novel assessment method for measurement of consistency of individual, text-valued attributes is proposed. The first novelty of this method is that it allows to express a broad range of wellknown consistency measurements in a simple, elegant and standardized way. This property is obtained by relying on the standardized framework of regular expressions to support measurement. The key advantage of using such a highly standardized expression syntax, is that knowledge about consistency becomes portable, exchangeable and easy to access. The second novelty of the method, is that it examines the advantages of using a finite and ordinal scale for expression of measurement. These advantages include a high degree of interpretation and efficient calculations both in terms of time and space complexity.
Keywords
Data quality, Regular expressions, Ordinal measurement

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Chicago
Bronselaer, Antoon, Joachim Nielandt, Robin De Mol, and Guy De Tré. 2016. “Ordinal Assessment of Data Consistency Based on Regular Expressions.” In INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS, IPMU 2016, PT II , ed. Joao Paulo Carvalho, Marie-Jeanne Lesot, Uzay Kaymak, Susana Vieira, Bernadette Bouchon-Meunier, and Ronald R Yager, 611:317–328. Switzerland: Springer.
APA
Bronselaer, Antoon, Nielandt, J., De Mol, R., & De Tré, G. (2016). Ordinal assessment of data consistency based on regular expressions. In J. P. Carvalho, M.-J. Lesot, U. Kaymak, S. Vieira, B. Bouchon-Meunier, & R. R. Yager (Eds.), INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS, IPMU 2016, PT II (Vol. 611, pp. 317–328). Presented at the IPMU 2016, Switzerland: Springer.
Vancouver
1.
Bronselaer A, Nielandt J, De Mol R, De Tré G. Ordinal assessment of data consistency based on regular expressions. In: Carvalho JP, Lesot M-J, Kaymak U, Vieira S, Bouchon-Meunier B, Yager RR, editors. INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS, IPMU 2016, PT II . Switzerland: Springer; 2016. p. 317–28.
MLA
Bronselaer, Antoon, Joachim Nielandt, Robin De Mol, et al. “Ordinal Assessment of Data Consistency Based on Regular Expressions.” INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS, IPMU 2016, PT II . Ed. Joao Paulo Carvalho et al. Vol. 611. Switzerland: Springer, 2016. 317–328. Print.
@inproceedings{7898032,
  abstract     = {In this paper, a novel assessment method for measurement of consistency of individual, text-valued attributes is proposed. The first novelty of this method is that it allows to express a broad range of wellknown consistency measurements in a simple, elegant and standardized way. This property is obtained by relying on the standardized framework of regular expressions to support measurement. The key advantage of using such a highly standardized expression syntax, is that knowledge about consistency becomes portable, exchangeable and easy to access. The second novelty of the method, is that it examines the advantages of using a finite and ordinal scale for expression of measurement. These advantages include a high degree of interpretation and efficient calculations both in terms of time and space complexity.},
  author       = {Bronselaer, Antoon and Nielandt, Joachim and De Mol, Robin and De Tr{\'e}, Guy},
  booktitle    = {INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS, IPMU 2016, PT II },
  editor       = {Carvalho, Joao Paulo and Lesot, Marie-Jeanne and Kaymak, Uzay and Vieira, Susana and Bouchon-Meunier, Bernadette and Yager, Ronald R},
  isbn         = {978-3-319-40580-3},
  issn         = {1865-0929 },
  language     = {eng},
  location     = {Eindhoven, The Netherlands},
  number       = {2},
  pages        = {317--328},
  publisher    = {Springer},
  title        = {Ordinal assessment of data consistency based on regular expressions},
  url          = {http://dx.doi.org/10.1007/978-3-319-40581-0\_26},
  volume       = {611},
  year         = {2016},
}

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