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On Hash Bipolar Division: An Enhanced Processing of Novel and Conventional Forms of Bipolar Division

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Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations (IPMU 2018)

Abstract

In this paper, two issues of bipolar division are discussed. First, we outline some new operators dealing with the bipolar division, to enrich the interpretations of bipolar queries. In this context, we propose some extended operators of bipolar division based on the connector “or else”. Besides, we introduce a new bipolar division operator dealing with the “Satisfied-Dissatisfied approach”. Secondly, we highlight the matter of the performance improvement of the considered operators. Thus, we present an efficient method which allows handling several bipolar divisions with a unified processing. Our idea is to design new variants of the classical Hash-Division algorithm, for dealing with the bipolar division. The issue of answers ranking is also dealt with. Computational experiments are carried out and demonstrate that the new variants outperform the conventional ones with respect to performance.

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Notes

  1. 1.

    Each tuple t in a fuzzy bipolar relation r is attached with a pair of grades \((\mu _c(t), \mu _w(t))\) that expresses the degree of its satisfaction respectively to the constraint c and the wish w [10].

  2. 2.

    In case \(s_1 \subset s_2\) the two subsets considered are \(s_{1}\) and \(s_{1}-s_{2}\).

  3. 3.

    In the literature, to the best of our knowledge, the largest set used in the experimentations never exceed a cardinality of 30000 tuples in the dividend relation.

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Correspondence to Noussaiba Benadjimi .

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Benadjimi, N., Hidouci, W., Hadjali, A. (2018). On Hash Bipolar Division: An Enhanced Processing of Novel and Conventional Forms of Bipolar Division. In: Medina, J., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations. IPMU 2018. Communications in Computer and Information Science, vol 853. Springer, Cham. https://doi.org/10.1007/978-3-319-91473-2_63

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  • DOI: https://doi.org/10.1007/978-3-319-91473-2_63

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  • Online ISBN: 978-3-319-91473-2

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