Abstract
In our previous work we have proposed the concept of a contextual bipolar linguistic summary. It is an extension of the seminal concept of a linguistic summary proposed by Yager which is based on the application of Zadeh’s calculus of linguistically quantified propositions to more intuitive and human consistent data mining. The original Yager’s concept evolved over the years and our recent contribution to this theory is the inclusion of the concept of bipolarity of information and preferences. This enrichment of the notion of the linguistic summary calls for specialized measures of its quality, interestingness, etc. We further study this problem and in this paper we propose a new approach to assessing the quality of this type of summaries.
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Acknowledgments
Mateusz Dziedzic contribution is supported by the Foundation for Polish Science under International PhD Projects in Intelligent Computing. Project financed from The European Union within the Innovative Economy Operational Programme (2007–2013) and European Regional Development Fund. This work was also partially supported by the National Science Centre (NCN) under Grant No. UMO-2012/05/B/ST6/03068.
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Dziedzic, M., Kacprzyk, J., Zadrożny, S., De Tré, G. (2016). Quantified Quality Criteria of Contextual Bipolar Linguistic Summaries. In: Trė, G., Grzegorzewski, P., Kacprzyk, J., Owsiński, J., Penczek, W., Zadrożny, S. (eds) Challenging Problems and Solutions in Intelligent Systems. Studies in Computational Intelligence, vol 634. Springer, Cham. https://doi.org/10.1007/978-3-319-30165-5_7
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