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Dealing with missing information in linguistic summarization: a bipolar approach

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Abstract
Linguistic summaries of databases provide quick insight in the stored data and are important facilities for understanding and grasping the meaning of large data collections. This is especially relevant in the context of big data. However, large data collections often suffer from incomplete data, which are in the case of relational databases modelled by so-called null-values. In this paper we propose a novel soft computing technique for measuring the quality of a linguistic summary in the case of missing information. More specifically we describe and illustrate how bipolar satisfaction degrees can be used to model both the validity of the summary and the hesitation about this validity that might be caused due to missing information. The extra information about the hesitation provides the users with a semantically richer description of the summarization results, which is important in view of a correct interpretation.
Keywords
DATABASES, TIME-SERIES, Linguistic summaries, databases, fuzzy sets, bipolarity

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Chicago
De Tré, Guy, Mateusz Dziedzic, Daan Van Britsom, and Slawomir Zadrozny. 2014. “Dealing with Missing Information in Linguistic Summarization: a Bipolar Approach.” In Advances in Intelligent Systems and Computing, ed. P Angelov, KT Atanassov, L Doukovska, M Hadjiski, V Jotsov, J Kacprzyk, N Kasabov, S Sotirov, E Szmidt, and S Zadrozny, 322:57–68. Switzerland: Springer.
APA
De Tré, G., Dziedzic, M., Van Britsom, D., & Zadrozny, S. (2014). Dealing with missing information in linguistic summarization: a bipolar approach. In P Angelov, K. Atanassov, L. Doukovska, M. Hadjiski, V. Jotsov, J. Kacprzyk, N. Kasabov, et al. (Eds.), Advances in Intelligent Systems and Computing (Vol. 322, pp. 57–68). Presented at the 7th IEEE International Conference on Intelligent Systems (IEEE IS), Switzerland: Springer.
Vancouver
1.
De Tré G, Dziedzic M, Van Britsom D, Zadrozny S. Dealing with missing information in linguistic summarization: a bipolar approach. In: Angelov P, Atanassov K, Doukovska L, Hadjiski M, Jotsov V, Kacprzyk J, et al., editors. Advances in Intelligent Systems and Computing. Switzerland: Springer; 2014. p. 57–68.
MLA
De Tré, Guy, Mateusz Dziedzic, Daan Van Britsom, et al. “Dealing with Missing Information in Linguistic Summarization: a Bipolar Approach.” Advances in Intelligent Systems and Computing. Ed. P Angelov et al. Vol. 322. Switzerland: Springer, 2014. 57–68. Print.
@inproceedings{5721217,
  abstract     = {Linguistic summaries of databases provide quick insight in the stored data and are important facilities for understanding and grasping the meaning of large data collections. This is especially relevant in the context of big data. However, large data collections often suffer from incomplete data, which are in the case of relational databases modelled by so-called null-values. In this paper we propose a novel soft computing technique for measuring the quality of a linguistic summary in the case of missing information. More specifically we describe and illustrate how bipolar satisfaction degrees can be used to model both the validity of the summary and the hesitation about this validity that might be caused due to missing information. The extra information about the hesitation provides the users with a semantically richer description of the summarization results, which is important in view of a correct interpretation.},
  author       = {De Tr{\'e}, Guy and Dziedzic, Mateusz and Van Britsom, Daan and Zadrozny, Slawomir},
  booktitle    = {Advances in Intelligent Systems and Computing},
  editor       = {Angelov, P and Atanassov, KT and Doukovska, L and Hadjiski, M and Jotsov, V and Kacprzyk, J and Kasabov, N and Sotirov, S and Szmidt, E and Zadrozny, S},
  isbn         = {9783319113128},
  language     = {eng},
  location     = {Warsaw, Poland},
  pages        = {57--68},
  publisher    = {Springer},
  title        = {Dealing with missing information in linguistic summarization: a bipolar approach},
  url          = {http://dx.doi.org/10.1007/978-3-319-11313-5},
  volume       = {322},
  year         = {2014},
}

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