2016
DOI: 10.3390/info7020022
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An Approach to the Match between Experts and Users in a Fuzzy Linguistic Environment

Abstract: Knowledge management systems are widely used to manage the knowledge in organizations. Consulting experts is an effective way to utilize tacit knowledge. The paper aims to optimize the match between users and experts to improve the efficiency of tacit knowledge-sharing. Firstly, expertise, trust and feedback are defined to characterize the preference of users for experts. Meanwhile, factors including trust, relationship and knowledge distance are defined to characterize the preference of experts for users. The… Show more

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Cited by 4 publications
(4 citation statements)
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“…Also very promising is the use of fuzzy logic techniques in intelligent expert assessment and classification systems with predictive function. In turn, Experts and future users should work out the optimal model of interaction [19].…”
Section: Methodsmentioning
confidence: 99%
“…Also very promising is the use of fuzzy logic techniques in intelligent expert assessment and classification systems with predictive function. In turn, Experts and future users should work out the optimal model of interaction [19].…”
Section: Methodsmentioning
confidence: 99%
“…In addition, experts are the source of tacit knowledge and their satisfaction determines effects of tacit knowledge sharing (Riege, 2005;Tamer Cavusgil et al, 2003). To satisfy both experts' and demanders' preferences simultaneously, the matching method is proposed with two-sided satisfaction (Li and Yuan, 2016). In the method, based on the assumption that one expert is Fuzzy linguistic environments matched with one demander, the optimization model is constructed to derive the optimal match with maximum overall satisfaction.…”
Section: Introductionmentioning
confidence: 99%
“…Examples of multibody systems can be found in several engineering applications [16][17][18][19][20]. The complexity of the dynamic behavior of this family of constrained mechanical systems requires the development of advanced analysis and modeling tools to perform virtual prototyping in the multibody framework [21][22][23][24][25][26][27]. The problem is particularly challenging when control strategies for flexible multibody systems need to be designed [28][29][30][31][32][33].…”
Section: Introductionmentioning
confidence: 99%