An Induced Hesitant Linguistic Aggregation Operator and Its Application for Creating Fuzzy Ontology
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kong, Mingming | - |
dc.contributor.author | Ren, Fangling | - |
dc.contributor.author | Park, Doo-Soon | - |
dc.contributor.author | Hao, Fei | - |
dc.contributor.author | Pei, Zheng | - |
dc.date.accessioned | 2021-08-11T11:43:34Z | - |
dc.date.available | 2021-08-11T11:43:34Z | - |
dc.date.issued | 2018-10-31 | - |
dc.identifier.issn | 1976-7277 | - |
dc.identifier.issn | 1976-7277 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/5569 | - |
dc.description.abstract | An induced hesitant linguistic aggregation operator is investigated in the paper, in which, hesitant fuzzy linguistic evaluation values are associated with probabilistic information. To deal with these hesitant fuzzy linguistic information, an induced hesitant fuzzy linguistic probabilistic ordered weighted averaging (IHFLPOWA) operator is proposed, monotonicity, boundary and idempotency of IHFLPOWA are proved. Then andness, orness and the entropy of dispersion of IHFLPOWA are analyzed, which are used to characterize the weighting vector of the operator, these properties show that IHFLPOWA is extensions of the induced linguistic ordered weighted averaging operator and linguistic probabilistic aggregation operator. In this paper, IHFLPOWA is utilized to gather linguistic information and create fuzzy ontologies, and a movie fuzzy ontology as an illustrative case study is used to show the elaboration of the proposed method and comparison with the existing linguistic aggregation operators, it seems that the IHFLPOWA operator is an useful and alternative operator for dealing with hesitant fuzzy linguistic information with probabilistic information. | - |
dc.format.extent | 24 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | 한국인터넷정보학회 | - |
dc.title | An Induced Hesitant Linguistic Aggregation Operator and Its Application for Creating Fuzzy Ontology | - |
dc.type | Article | - |
dc.publisher.location | 대한민국 | - |
dc.identifier.doi | 10.3837/tiis.2018.10.018 | - |
dc.identifier.scopusid | 2-s2.0-85057230903 | - |
dc.identifier.wosid | 000448833400018 | - |
dc.identifier.bibliographicCitation | KSII Transactions on Internet and Information Systems, v.12, no.10, pp 4952 - 4975 | - |
dc.citation.title | KSII Transactions on Internet and Information Systems | - |
dc.citation.volume | 12 | - |
dc.citation.number | 10 | - |
dc.citation.startPage | 4952 | - |
dc.citation.endPage | 4975 | - |
dc.type.docType | Article | - |
dc.identifier.kciid | ART002401760 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordPlus | GROUP DECISION-MAKING | - |
dc.subject.keywordPlus | TERM SETS | - |
dc.subject.keywordPlus | REPRESENTATION MODEL | - |
dc.subject.keywordPlus | DISTANCE | - |
dc.subject.keywordPlus | WEIGHTS | - |
dc.subject.keywordAuthor | Hesitant fuzzy linguistic terms set | - |
dc.subject.keywordAuthor | 2-tuple linguistic model | - |
dc.subject.keywordAuthor | linguistic multi-criteria group decision making | - |
dc.subject.keywordAuthor | fuzzy ontology | - |
dc.subject.keywordAuthor | linguistic probabilistic aggregation operator | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(31538) 22, Soonchunhyang-ro, Asan-si, Chungcheongnam-do, Republic of Korea+82-41-530-1114
COPYRIGHT 2021 by SOONCHUNHYANG UNIVERSITY ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.