Multiple multidimensional linguistic reasoning algorithm based on property-oriented linguistic concept lattice

Cui, Hui; Yue, Guanli; Zou, Li; Liu, Xin; Deng, Ansheng

doi:10.1016/j.ijar.2020.11.006

Cited by 14 publications

(3 citation statements)

References 31 publications

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“…In order to represent the complex hierarchical relationships between linguistic values, several scholars attempted to embed fuzzy linguistic information into the concept lattice [47][48][49][50][51]. For instance, Zou et al [47,48,52] proposed corresponding linguistic concept lattices based on various fuzzy linguistic representation models and applied them to such tasks as rule mining, attribute approximation, and decision making. Linguistic truthvalued lattice implication algebra used lattice implication algebra to model evaluative linguistic expressions, which could handle comparable and incomparable evaluative linguistic expressions.…”

Section: Introductionmentioning

confidence: 99%

Association rule mining with fuzzy linguistic information based on attribute partial ordered structure

Pang

et al. 2023

Preprint

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Numerous linguistically valued facts from the actual world have been modeled using the fuzzy linguistic approaches. Data owners urgently need to mine attribute associations hidden in linguistic concept knowledge. In order to solve the problem of association rule mining with fuzzy linguistic information, this paper proposes an association rule mining approach based on fuzzy linguistic attribute partial ordered structure diagram. Firstly, complex relationships between linguistic values in association rule mining are represented by fuzzy linguistic association nodes and association paths via fuzzy linguistic attribute partial ordered structure diagram (FL-APOSD). On this basis, the maximum frequent attribute set is mined from the FL-APOSD, and then the non-redundancy association rules are extracted. Secondly, in order to show the information hidden in the rules and help users to deeply understand the mining results, a fuzzy linguistic association rule visualization approach is proposed to convert the association rules into the FL-APOSD-based knowledge representation. Finally, experimental results on real-world datasets show the proposed approach's high efficiency, outperforming two relevant state-of-the-art approaches.

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Section: Introductionmentioning

confidence: 99%

Association rule mining with fuzzy linguistic information based on attribute partial ordered structure

Pang

et al. 2023

Preprint

Self Cite

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“…Concept lattice [1] is widely used in many fields [2][3][4], such as information retrieval, software engineering, recommendation systems, and knowledge discovery. It has made some achievements in knowledge reduction [1,5], rule extraction [6,7], decision analysis [8,9], and uncertainty reasoning [10,11], among others [12][13][14]. Concept lattice can be used to discover implicit concepts and their relationships, which can visualize acquired information.…”

Section: Introductionmentioning

confidence: 99%

Construction of Fuzzy Linguistic Approximate Concept Lattice in an Incomplete Fuzzy Linguistic Formal Context

Yang

Jia³

et al. 2022

Int J Comput Intell Syst

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Uncertainty research is one of the critical problems in artificial intelligence. In an uncertain environment, a large quantity of information is expressed in linguistic values. Aiming at the missing linguistic-valued information, we first propose incomplete fuzzy linguistic formal context and then discuss the fuzzy linguistic approximate concept. Our proposal can describe the attributes of objects from two aspects simultaneously. One is an object's essential attributes, and another includes the essential and possible attributes. As a result, more object-related information can be obtained to reduce information loss effectively. We design a similarity metric for correcting the errors caused by the initial complement operation. We then construct a corresponding fuzzy linguistic approximate concept lattice for the task of approximate information retrieval. Finally, we illustrate the applicability and feasibility of the proposed approach with concrete examples, which clearly show that our approach can better deal with the linguistic-valued information in an uncertain environment.

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“…Nowadays, people punch in and out of work using fingerprint identification, which avoids the need to wait in a queue for a long time; such an arrangement not only saves each worker's time but also ensures that the company does not need to maintain or rely on any manual record of attendance, and that absentees, latecomers and early leavers can be known at a glance. Scanning code payment and scanning code collection are achieved everywhere by a mobile phone [1], which saves people a lot of unnecessary trouble and makes their lives tend to be simplified and convenient. At the same time, 'talking' robots can sing, tell jokes and chat with people, which relieves people's mental stress [2].…”

Section: Introductionmentioning

confidence: 99%

Research on rule extraction method based on concept lattice of intuitionistic fuzzy language

Yan¹

2022

Applied Mathematics and Nonlinear Sciences

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Studying the concept lattice of intuitionistic fuzzy language can not only enable an intuitive expression of the relationship between objects and attributes but also ensure the effectiveness of information, and it thus provides a new idea for the development of artificial intelligence. Therefore, in this paper, the rule extraction method is studied based on the concept lattice of intuitionistic fuzzy language. By combining the formal context of intuitionistic fuzzy language with the context of decision formal, the formal context of intuitionistic fuzzy language decision is put forward and the rule extraction method under this context is constructed. The problem of decision making in real life can be solved through the weighted similarity in the formal context of intuitionistic fuzzy language.

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Multiple multidimensional linguistic reasoning algorithm based on property-oriented linguistic concept lattice

Cited by 14 publications

References 31 publications

Association rule mining with fuzzy linguistic information based on attribute partial ordered structure

Association rule mining with fuzzy linguistic information based on attribute partial ordered structure

Construction of Fuzzy Linguistic Approximate Concept Lattice in an Incomplete Fuzzy Linguistic Formal Context

Research on rule extraction method based on concept lattice of intuitionistic fuzzy language

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