Construction of Fuzzy Linguistic Approximate Concept Lattice in an Incomplete Fuzzy Linguistic Formal Context
Abstract 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 a...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Springer
2022-08-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44196-022-00125-1 |
| _version_ | 1817998917654020096 |
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| author | Dongqiang Yang Xinran Yang Hui Jia Lixian Xu Jin Guo |
| author_facet | Dongqiang Yang Xinran Yang Hui Jia Lixian Xu Jin Guo |
| author_sort | Dongqiang Yang |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-04-14T03:00:42Z |
| format | Article |
| id | doaj.art-cd84cd672a4d46a8afb404ffcecc0df8 |
| institution | Directory Open Access Journal |
| issn | 1875-6883 |
| language | English |
| last_indexed | 2024-04-14T03:00:42Z |
| publishDate | 2022-08-01 |
| publisher | Springer |
| record_format | Article |
| series | International Journal of Computational Intelligence Systems |
| spelling | doaj.art-cd84cd672a4d46a8afb404ffcecc0df82022-12-22T02:15:56ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832022-08-011511910.1007/s44196-022-00125-1Construction of Fuzzy Linguistic Approximate Concept Lattice in an Incomplete Fuzzy Linguistic Formal ContextDongqiang Yang0Xinran Yang1Hui Jia2Lixian Xu3Jin Guo4School of Computer Science and Technology, Shandong Jianzhu UniversitySchool of Computer and Information Technology, Liaoning Normal UniversityBaita District Erdaojie Primary School of LiaoyangSchool of Computer Science and Technology, Shandong Jianzhu UniversitySchool of Computer and Information Technology, Liaoning Normal UniversityAbstract 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.https://doi.org/10.1007/s44196-022-00125-1Incomplete formal contextApproximate conceptConcept latticeFuzzy linguistic approximate concept |
| spellingShingle | Dongqiang Yang Xinran Yang Hui Jia Lixian Xu Jin Guo Construction of Fuzzy Linguistic Approximate Concept Lattice in an Incomplete Fuzzy Linguistic Formal Context International Journal of Computational Intelligence Systems Incomplete formal context Approximate concept Concept lattice Fuzzy linguistic approximate concept |
| title | Construction of Fuzzy Linguistic Approximate Concept Lattice in an Incomplete Fuzzy Linguistic Formal Context |
| title_full | Construction of Fuzzy Linguistic Approximate Concept Lattice in an Incomplete Fuzzy Linguistic Formal Context |
| title_fullStr | Construction of Fuzzy Linguistic Approximate Concept Lattice in an Incomplete Fuzzy Linguistic Formal Context |
| title_full_unstemmed | Construction of Fuzzy Linguistic Approximate Concept Lattice in an Incomplete Fuzzy Linguistic Formal Context |
| title_short | Construction of Fuzzy Linguistic Approximate Concept Lattice in an Incomplete Fuzzy Linguistic Formal Context |
| title_sort | construction of fuzzy linguistic approximate concept lattice in an incomplete fuzzy linguistic formal context |
| topic | Incomplete formal context Approximate concept Concept lattice Fuzzy linguistic approximate concept |
| url | https://doi.org/10.1007/s44196-022-00125-1 |
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