کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
404983 677469 2015 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Knowledge reduction in formal fuzzy contexts
ترجمه فارسی عنوان
کاهش دانش در زمینه های فازی رسمی
کلمات کلیدی
مفهوم مخازن، ماتریس قابل تشخیص، زمینه فازی رسمی، کاهش دانش، آستانه متغیر
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• We proposed a general method of knowledge reduction in formal fuzzy contexts.
• We gave some judging methods of attribute characteristics in fomal fuzzy contexts.
• We constucted the discernibility functions to calculating the attribute reducts.

Knowledge reduction is a basic issue in knowledge representation and data mining. Although various methods have been developed to reduce the size of classical formal contexts, the reduction of formal fuzzy contexts based on fuzzy lattices remains a difficult problem owing to its complicated derivation operators. To address this problem, we propose a general method of knowledge reduction by reducing attributes and objects in formal fuzzy contexts based on the variable threshold concept lattices. Employing the proposed approaches, we remove attributes and objects which are non-essential to the structure of a variable threshold concept lattice, i.e., with a given threshold level, the concept lattice constructed from a reduced formal context is made identical to that constructed from the original formal context. Discernibility matrices and Boolean functions are, respectively, employed to compute the attribute reducts and object reducts of the formal fuzzy contexts, by which all the attribute reducts and object reducts of the formal fuzzy contexts are determined without changing the structure of the lattice.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 73, January 2015, Pages 265–275
نویسندگان
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