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Extracting Fuzzy Linguistic Summaries Based on Including Degree Theory and FCA

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Foundations of Fuzzy Logic and Soft Computing (IFSA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4529))

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Abstract

In information systems (or database), generally, attribute values of objects are numeral or symbols, from application point of view, linguistic information or decision rules are widely used. Hence, fuzzy linguistic summaries would be very desirable and human consistent. In this paper, extracting fuzzy linguistic summaries from a continuous information system is discussed. Due to fuzzy linguistic summaries can not be extracted directly in the information system, fuzzy information system is used to discretize the continuous information system, and level cut set is used to obtain classical information system firstly. Then based on including degree theory and formal concept analysis (FCA), simple fuzzy linguistic summaries are extracted. To extract complex linguistic summaries, logical conjunctions ∨ , ∧ and → are used. An Example of checking quality of sweetened full cream milk powder is also provided.

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Patricia Melin Oscar Castillo Luis T. Aguilar Janusz Kacprzyk Witold Pedrycz

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Zhang, L., Pei, Z., Chen, H. (2007). Extracting Fuzzy Linguistic Summaries Based on Including Degree Theory and FCA. In: Melin, P., Castillo, O., Aguilar, L.T., Kacprzyk, J., Pedrycz, W. (eds) Foundations of Fuzzy Logic and Soft Computing. IFSA 2007. Lecture Notes in Computer Science(), vol 4529. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72950-1_28

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  • DOI: https://doi.org/10.1007/978-3-540-72950-1_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72917-4

  • Online ISBN: 978-3-540-72950-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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