Open Access
ARTICLE
Multidimensional Quality Evaluation of Graduate Thesis: Based on the Probabilistic Linguistic MABAC Method
Yuyan Luo1,2, Xiaoxu Zhang1,*, Tao Tong1, Yong Qin3,*, Zheng Yang1
1
College of Management Science, Chengdu University of Technology, Chengdu, 610059, China
2
Post-Doctorate R&D Base of Management Science and Engineering, Chengdu University of Technology, Chengdu, 610059, China
3
Business School, Sichuan University, Chengdu, 610064, China
* Corresponding Authors: Xiaoxu Zhang. Email: ; Yong Qin. Email:
(This article belongs to the Special Issue: Linguistic Approaches for Multiple Criteria Decision Making and Applications)
Computer Modeling in Engineering & Sciences 2023, 137(2), 2049-2076. https://doi.org/10.32604/cmes.2023.025413
Received 11 July 2022; Accepted 10 February 2023; Issue published 26 June 2023
Abstract
Graduate education is the main way to train high-level innovative talents, the basic layout to cope with the
global talent competition, and the important cornerstone for implementing the innovation-driven development
strategy and building an innovation-driven country. Therefore, graduate education is of great remarkably to the
development of national education. As an important manifestation of graduate education, the quality of a graduate
thesis should receive more attention. It is conducive to promoting the quality of graduates by supervising and
examining the quality of the graduate thesis. For this purpose, this work is based on text mining, expert interviews,
and questionnaire surveys to obtain the factors influencing the quality of a graduate thesis first. Then, through three
rounds of expert consultation, a multidimensional evaluation indicator system for the graduate thesis quality is
built. Furthermore, probabilistic linguistic term sets (PLTSs) are utilized to obtain the initial evaluation information
and apply the stepwise weight assessment ratio analysis method to determine the weights of attributes. In the
ensuing step, the novel multi-attribute border approximation area comparison based on the PLTS method is
established. Finally, the proposed method is employed in a case study concerning the quality evaluation of a
graduate thesis and the effectiveness of this approach is further illustrated.
Keywords
Cite This Article
APA Style
Luo, Y., Zhang, X., Tong, T., Qin, Y., Yang, Z. (2023). Multidimensional quality evaluation of graduate thesis: based on the probabilistic linguistic MABAC method. Computer Modeling in Engineering & Sciences, 137(2), 2049-2076. https://doi.org/10.32604/cmes.2023.025413
Vancouver Style
Luo Y, Zhang X, Tong T, Qin Y, Yang Z. Multidimensional quality evaluation of graduate thesis: based on the probabilistic linguistic MABAC method. Comput Model Eng Sci. 2023;137(2):2049-2076 https://doi.org/10.32604/cmes.2023.025413
IEEE Style
Y. Luo, X. Zhang, T. Tong, Y. Qin, and Z. Yang "Multidimensional Quality Evaluation of Graduate Thesis: Based on the Probabilistic Linguistic MABAC Method," Comput. Model. Eng. Sci., vol. 137, no. 2, pp. 2049-2076. 2023. https://doi.org/10.32604/cmes.2023.025413