scholarly journals Generalization of String Transformation Rules using Optimized Concept Lattice Construction Method

2017 ◽  
Vol 181 ◽  
pp. 604-611 ◽  
Author(s):  
László Kovács ◽  
Szabó Gábor
2021 ◽  
Vol 82 (2) ◽  
Author(s):  
Sándor Radeleczki

AbstractG. Czédli proved that the blocks of any compatible tolerance T of a lattice L can be ordered in such a way that they form a lattice L/T called the factor lattice of L modulo T. Here we show that the Dedekind–MacNeille completion of the lattice L/T is isomorphic to the concept lattice of the context (L, L, R), where R stands for the reflexive weak ordered relation $$ \mathord {\le } \circ T$$ ≤ ∘ T . Weak ordered relations constitute the generalization of the ordered relations introduced by S. Valentini. Reflexive weak ordered relations can be characterized as compatible reflexive relations $$R\subseteq L^{2}$$ R ⊆ L 2 satisfying $$R=\ \mathord {\le } \circ R\circ \mathord {\le } $$ R = ≤ ∘ R ∘ ≤ .


Information ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 78 ◽  
Author(s):  
Jingpu Zhang ◽  
Ronghui Liu ◽  
Ligeng Zou ◽  
Licheng Zeng

Formal concept analysis has proven to be a very effective method for data analysis and rule extraction, but how to build formal concept lattices is a difficult and hot topic. In this paper, an efficient and rapid incremental concept lattice construction algorithm is proposed. The algorithm, named FastAddExtent, is seen as a modification of AddIntent in which we improve two fundamental procedures, including fixing the covering relation and searching the canonical generator. The proposed algorithm can locate the desired concept quickly by adding data fields to every concept. The algorithm is depicted in detail, using a formal context to show how the new algorithm works and discussing time and space complexity issues. We also present an experimental evaluation of its performance and comparison with AddExtent. Experimental results show that the FastAddExtent algorithm can improve efficiency compared with the primitive AddExtent algorithm.


IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 146838-146847
Author(s):  
Congfei Sun ◽  
Kaixi Wang

2011 ◽  
Vol 63-64 ◽  
pp. 664-667
Author(s):  
Hong Sheng Xu ◽  
Ting Zhong Wang

Formal concept lattices and rough set theory are two kinds of complementary mathematical tools for data analysis and data processing. The algorithm of concept lattice reduction based on variable precision rough set is proposed by combining the algorithms of β-upper and lower distribution reduction in variable precision rough set. The traditional algorithms aboutβvalue select algorithm, attribute reduction based on discernibility matrix and extraction rule in VPRS are discussed, there are defects in these traditional algorithms which are improved. Finally, the generation system of concept lattice based on variable precision rough set is designed to verify the validity of the improved algorithm and a case demonstrates the whole process of concept lattice construction.


2013 ◽  
Vol 756-759 ◽  
pp. 1729-1733
Author(s):  
Ya Feng Yang ◽  
Dong Mei Li ◽  
Wen Jing Zhao

From the view of fuzzy cut set, the fuzzy concept lattice was analyzed and researched and a new kind of concept lattice was proposed. The concept lattice with every different confidence can be constructed through selecting different level of . From two different angles of context and concept, two corresponding construction methods, context cut method and concept cut method, were discussed, and some results were given. Furthermore, an example was provided to illustrate the method correct.


Sign in / Sign up

Export Citation Format

Share Document