Research on multi-criteria decision-making method based on heterogeneous online reviews

被引:0
|
作者
He S. [1 ]
Pan X. [2 ]
Wang Y. [1 ]
机构
[1] School of Economics and Management, Fuzhou University, Fuzhou
[2] Business School, Qingdao University, Qingdao
基金
中国国家自然科学基金;
关键词
heterogeneous information processing; heterogeneous online reviews; information fusion; interval weight determination; multi-criteria decision making;
D O I
10.12011/SETP2023-0518
中图分类号
学科分类号
摘要
With the development of information technology, a large amount of valuable information has been accumulated in the Internet, which has become an important source of information in multi-criteria decision-making (MCDM). Due to the differences of personal knowledge background, experience, expression habits, and different criteria characteristics, online reviews usually consists of many forms of information, such as crisp numbers, interval numbers, and text. This heterogeneity of information will bring new challenges to information processing, fusion and alternative selection in the decision process. In order to address these challenges, a MCDM method based on heterogeneous online reviews is proposed. First, heterogeneous online reviews related to decision-making problems are obtained through data acquisition and preprocessing methods. Then, a heterogeneous information processing method is proposed to uniformly process these different forms of information into linguistic distribution information. Next, in order to cope with the ambiguity and uncertainty in online information, an interval weight determination model and an information fusion method based on evidence reasoning algorithm are proposed. Finally, the practicality and validity are verified by a case study regarding vehicle evaluation. © 2024 Systems Engineering Society of China. All rights reserved.
引用
收藏
页码:1349 / 1364
页数:15
相关论文
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  • [1] Liu B S, Zhou Q, Ding R X, Et al., Large-scale group decision making model based on social network analysis: Trust relationship-based conflict detection and elimination[J], European Journal of Operational Research, 275, 2, pp. 737-754, (2019)
  • [2] Wang Y M, He S F, Garcia Zamora D, Et al., A large scale group three-way decision-based consensus model for site selection of new energy vehicle charging stations, Expert Systems with Applications, 214, (2023)
  • [3] Dwivedi A, Pant R., An algorithmic implementation of entropic ternary reduct soft sentiment set (ETRSSS) using soft computing technique on big data sentiment analysis (BDSA) for optimal selection of a decision based on real-time update in online reviews[J], Journal of King Saud University—Computer and Information Sciences, 34, 5, pp. 2118-2130, (2022)
  • [4] Zhang C X, Zhao M, Cai M Y, Et al., Multi-stage multi-attribute decision making method based on online reviews for hotel selection considering the aspirations with different development speeds, Computers & Industrial Engineering, 143, (2020)
  • [5] Darko A P, Liang D C., Modeling customer satisfaction through online reviews: A flowsort group decision model under probabilistic linguistic settings, Expert Systems with Applications, 195, (2022)
  • [6] Liu Y, Bi J W, Fan Z P., Ranking products through online reviews: A method based on sentiment analysis technique and intuitionistic fuzzy set theory[J], Information Fusion, 36, pp. 149-161, (2017)
  • [7] Fan Z P, Xi Y, Liu Y., Supporting consumer’s purchase decision: A method for ranking products based on online multi-attribute product ratings[J], Soft Computing, 22, 16, pp. 5247-5261, (2017)
  • [8] He S F, Wang Y M, Pan X H, Et al., Decision analysis framework based on incomplete online textual reviews[J], Information Sciences, 584, pp. 701-718, (2022)
  • [9] Liu P D, Teng F., Probabilistic linguistic todim method for selecting products through online product reviews[J], Information Sciences, 485, pp. 441-455, (2019)
  • [10] Liang D C, Dai Z Y, Wang M W., Assessing customer satisfaction of O2O takeaway based on online reviews by integrating fuzzy comprehensive evaluation with AHP and probabilistic linguistic term sets, Applied Soft Computing, 98, (2021)