Novel Approach of Semantic Annotation by Fuzzy Ontology based on Variable Precision Rough Set and Concept Lattice

2016 ◽  
Vol 9 (4) ◽  
pp. 25-40 ◽  
Author(s):  
Hongsheng Xu ◽  
Ruiling Zhang ◽  
Chunjie Lin ◽  
Youzhong Ma
Keyword(s):  
Rough Set ◽  
Concept Lattice ◽  
Semantic Annotation ◽  
Variable Precision ◽  
Fuzzy Ontology ◽  
Novel Approach ◽  
Variable Precision Rough Set

The Research of Constructing Rough Concept Lattices Model

2011 ◽  
Vol 63-64 ◽  
pp. 664-667
Author(s):  
Hong Sheng Xu ◽  
Ting Zhong Wang
Keyword(s):  
Rough Set ◽  
Rough Set Theory ◽  
Concept Lattice ◽  
Attribute Reduction ◽  
Formal Concept ◽  
Concept Lattices ◽  
Variable Precision ◽  
Whole Process ◽  
Variable Precision Rough Set ◽  
Lattice Construction

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.

Constructing Domain Ontology of E-Business Based on Rough Concept Lattices

2011 ◽  
Vol 219-220 ◽  
pp. 202-205
Author(s):  
Hong Sheng Xu ◽  
Jia Song
Keyword(s):  
Rough Set ◽  
Formal Concept Analysis ◽  
Concept Lattice ◽  
Concept Analysis ◽  
Domain Ontology ◽  
Formal Context ◽  
Formal Concept ◽  
Variable Precision ◽  
Ontology Model ◽  
Variable Precision Rough Set

Variable precision rough set (VPRS) model and formal concept analysis are studied in this paper, include algorithm of reduction attribute and extraction rule. The traditional algorithms about attribute reduction based on discernibility matrix and extraction rule in VPRS are discussed, there are problems in these traditional algorithms which are improved. Rough concept lattice model is proposed based on integrating of variable precision rough set model and formal concept analysis, and is used to reduce formal context. The domain ontology model of e-business is built combined with knowledge of domain expert, and original ontology model of the United Nations Standard Products and Services Classification Code by way of core ontology in order to enhance system robustness and efficiency.

A New Rough Set Model and its Application

2014 ◽  
Vol 599-601 ◽  
pp. 1350-1356
Author(s):  
Ming Ming Jia ◽  
Hai Qin Qin ◽  
Yong Qi Wang ◽  
Ke Jun Xu
Keyword(s):  
Rough Set ◽  
Discrete Variables ◽  
Water Pump ◽  
Variable Precision ◽  
Engineering Problems ◽  
Neighborhood Rough Set ◽  
Variable Precision Rough Set ◽  
Robust To Noise

A new neighborhood variable precision rough set modal is presented in this paper. The modal possesses the characteristics of neighborhood rough set and variable precision rough set, so it can overcome shortcomings of classic rough set which only be fit for discrete variables and sensitive to noise. Based on giving the definitions of approximate reduction, lower and upper approximate reduction, lower and upper distribution reduction, two kinds of algorithms to confirm lower and upper distribution reduction were advanced. The modal was applied to diagnose one frequency modulated water pump vibration faults. The result shows the modal is more suitable to engineering problems, because it can not only deal with continues variables but also be robust to noise.

Incremental Approach for Updating Approximations of Variable Precision Rough Set Based on Dominance Relations

2014 ◽  
Vol 631-632 ◽  
pp. 49-52
Author(s):  
Yan Li ◽  
Jia Jia Hou ◽  
Xiao Qing Liu
Keyword(s):  
Information System ◽  
Rough Set ◽  
Dominance Relation ◽  
Incremental Updating ◽  
Dominance Relations ◽  
Incremental Approach ◽  
Variable Precision ◽  
Variable Precision Rough Set ◽  
Over Time

Variable precision rough set (VPRS) based on dominance relation is an extension of traditional rough set by which can handle preference-ordered information flexibly. This paper focuses on the maintenance of approximations in dominance based VPRS when the objects in an information system vary over time. The incremental updating principles are given as inserting or deleting an object, and some experimental evaluations validates the effectiveness of the proposed method.

Variable Precision Rough Set Model Based on Covering Relation and Uncertainty Measure

2013 ◽  
Vol 694-697 ◽  
pp. 2856-2859
Author(s):  
Mei Yun Wang ◽  
Chao Wang ◽  
Da Zeng Tian
Keyword(s):  
Rough Set ◽  
Uncertainty Measure ◽  
Probabilistic Measure ◽  
Covering Relation ◽  
Practical Applications ◽  
Variable Precision ◽  
Model Based ◽  
Equivalent Relation ◽  
Proposed Model ◽  
Variable Precision Rough Set

The variable precision probabilistic rough set model is based on equivalent relation and probabilistic measure. However, the requirements of equivalent relation and probabilistic measure are too strict to satisfy in some practical applications. In order to solve the above problem, a variable precision rough set model based on covering relation and uncertainty measure is proposed. Moreover, the upper and lower approximation operators of the proposed model are given, while the properties of the operators are discussed.

scholarly journals A Variable Precision Rough Set Model for Knowledge-assisted Management in Distance Education

2018 ◽  
Vol 13 (11) ◽  
pp. 41
Author(s):  
Wei Zhang
Keyword(s):  
Distance Education ◽  
Rough Set ◽  
Real Data ◽  
Knowledge Extraction ◽  
Data Conversion ◽  
Complete Reduction ◽  
Variable Precision ◽  
Noise Data ◽  
Variable Precision Rough Set ◽  
Assisted Management

To enable the teaching administrator to better obtain effective knowledge from a large amount of information to assist management and improve the efficiency and level of teaching management, a variable precision rough set model for knowledge assisted management of distance education was proposed. First, based on the theory of complete reduction and knowledge extraction, the proposed pedigree ambiguity tree was used as a strategy for obtaining complete reduction. An algorithm for obtaining a complete set of reductions was given. Then, by studying the process of knowledge extraction, a multi-knowledge extraction framework was put forward. The process of data conversion was completely realized. Finally, experimental verification was performed. The results showed that the proposed model overcame the effect of noise data in real data and improved the efficiency of the algorithm. Therefore, the model has high universality.

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