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Multimedia Tools and Applications

, Volume 78, Issue 21, pp 30975–31001 | Cite as

A method of multimedia teaching evaluation based on fuzzy linguistic concept lattice

  • Pengsen Liu
  • Hui Cui
  • Yiming Cao
  • Xuehui Hou
  • Li ZouEmail author
Article
  • 51 Downloads

Abstract

With the development of multimedia technology, multimedia based teaching has become a popular style for educations. However, multimedia teaching evaluation performance is not an easy task as it involves human decision making which is imprecise, vague and uncertain. In order to acquire the effect of multimedia teaching in incomplete formal context, this paper mainly focuses on an algorithm of rule extraction based on incomplete multi-expert fuzzy linguistic formal decision context. Specifically, we propose a kind of fuzzy linguistic concept lattice combining with fuzzy linguistic information in uncertainty linguistic environment. The corresponding confidence level, the support degree of linguistic decision rules in fuzzy linguistic decision concept are discussed. Based on fuzzy linguistic formal context, we construct a multi-expert fuzzy linguistic concept lattice to handle multi-expert linguistic evaluation information. To address the scenario that the experts’ weights are unknown, we present a maximization deviation method in multi-expert fuzzy linguistic formal context through the distance of linguistic evaluation matrix. Furthermore, we develop a linguistic aggregation operator of multi-expert fuzzy linguistic concept lattice to obtain the association rules. A novel linguistic completing method using similarity and average difference is proposed to deal with the information missing problem, which can make the linguistic evaluation information more compact and the decision results more reasonable. We validate the effectiveness and practicability of our method via an intuitive example of multimedia teaching evaluation.

Keywords

Fuzzy linguistic concept lattice Incomplete formal context Rule extraction Multimedia teaching evaluation 

Notes

Acknowledgements

This work is partially supported by the National Natural Science Foundation of P. R. China (Nos.61772250, 61673320, 61672127), the Fundamental Research Funds for the Central Universities (No. 2682017ZT12).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Glasgow CollegeUniversity of Electronic Science and Technology of ChinaChengduChina
  2. 2.School of MathematicsLiaoning Normal UniversityDalianChina
  3. 3.School of Computer and Information TechnologyLiaoning Normal UniversityDalianChina

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