Wyniki wyszukiwania - Biblioteka Nauki

1

A comprehensive survey on formal concept analysis, its research trends and applications

100%

Singh P. , Aswani Kumar C. , Gani A.

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tom 26

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nr 2

495-516

EN

In recent years, FCA has received significant attention from research communities of various fields. Further, the theory of FCA is being extended into different frontiers and augmented with other knowledge representation frameworks. In this backdrop, this paper aims to provide an understanding of the necessary mathematical background for each extension of FCA like FCA with granular computing, a fuzzy setting, interval-valued, possibility theory, triadic, factor concepts and handling incomplete data. Subsequently, the paper illustrates emerging trends for each extension with applications. To this end, we summarize more than 350 recent (published after 2011) research papers indexed in Google Scholar, IEEE Xplore, ScienceDirect, Scopus, SpringerLink, and a few authoritative fundamental papers.

2

Vector-based Attribute Reduction Method for Formal Contexts

100%

Shao M. , Liu M. , Guo L.

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tom Vol. 126, nr 4

397--414

EN

Attribute reduction is one basic issue in knowledge discovery of information systems. In this paper, based on the object oriented concept lattice and classical concept lattice, the approach of attribute reduction for formal contexts is investigated. We consider attribute reduction and attribute characteristics from the perspective of linear dependence of vectors. We first introduce the notion of context matrix and the operations of corresponding column vectors, then present some judgment theorems of attribute reduction for formal contexts. Furthermore, we propose a new method to reducing formal context and show corresponding reduction algorithms. Compared with previous reduction approaches which employ discernibility matrix and discernibility function to determine all reducts, the proposed approach is more simpler and easier to implement.

3

Research on Interval Concept Lattice and its Construction Algorithm

86%

Liu B. , Zhang C. , Yang Y.

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2013

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tom R. 89, nr 1b

1--6

EN

In classic concept lattice and rough concept lattice, the concept extents have all the attributes or only one attribute sometimes. So the support and confidence degree of the extracted association rules would be reduced greatly. To solve this problem, authors have put forward a new concept lattice structure: interval concept lattice Lαβ (Mα, Mβ,Y) based on the parameter interval [ α,β ] (0 ≤ α ≤ β ≤ 1). The concept extent is an object sets which meet the properties in the intent in the interval [ α,β ] 0 ≤ α ≤ β ≤ 1. It has been proved that interval concept lattice degenerate into classic concept lattice when ( α = β = 1), and when ( α > 0, β = 1), interval concept lattice degenerate into rough concept lattice. Then some unique properties of interval concept lattice have been proved. The construction algorithm of interval concept lattice was designed. Finally, the necessity and practicability were verified through a case study.

PL

W klasycznej i przybliżonej kracie pojęć ich obszar obejmuje każdy lub czasami tylko jeden atrybut. A więc podstawa i stopień poufności wydobywanych relacji mogą zostać poważnie zredukowane. Aby rozwiązać ten problem autorzy proponują nową strukturę kraty pojęć: przedziałową kratę pojęć Lαβ (Mα, Mβ,Y) zdefiniowaną w przedziale [ α,β ] (0 ≤ α ≤ β ≤ 1). Udowodniono, że przedziałowa krata pojęć przekształca się w klasyczną jeśli ( α = β = 1) i w przybliżoną gdy ( α > 0, β = 1). Zbadano unikalne własności kraty przedziałowej i zaprojektowano algorytm jej budowy. W końcu zweryfikowano , w przypadku studialnym, potrzebę jej wprowadzenia i możliwość wykonania.

4

A comprehensive survey on formal concept analysis, its research trends and applications

72%

Singh P. K. , Aswani Kumar C. , Gani A.

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2016

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tom Vol. 26, no. 2

495--516

EN

In recent years, FCA has received significant attention from research communities of various fields. Further, the theory of FCA is being extended into different frontiers and augmented with other knowledge representation frameworks. In this backdrop, this paper aims to provide an understanding of the necessary mathematical background for each extension of FCA like FCA with granular computing, a fuzzy setting, interval-valued, possibility theory, triadic, factor concepts and handling incomplete data. Subsequently, the paper illustrates emerging trends for each extension with applications. To this end, we summarize more than 350 recent (published after 2011) research papers indexed in Google Scholar, IEEE Xplore, ScienceDirect, Scopus, SpringerLink, and a few authoritative fundamental papers.