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The Interval probabilistic double hierarchy linguistic EDAS method based on natural language processing basic techniques and its application to hotel online reviews

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Abstract

In recent years, double hierarchy linguistic expression models have developed rapidly in the field of decision making because their rich semantics are closer to people’s actual language environment. However, the existing double hierarchy linguistic expression models are difficult to deal with incomplete or missing information application situations. For example, online reviews provide some references for consumers to make decisions, but the information of many reviews is not necessarily complete. Therefore, we try to solve this problem and propose the concept of interval probabilistic double hierarchy linguistic term set (IP-DHLTS). At the same time, in order to ensure stability under different criteria weights, we choose to combine the EDAS method to obtain the average solution based on two measures. To sum up, we develop the interval probabilistic double hierarchy linguistic EDAS method and solve a real case with the natural language processing basic techniques about the hotel online reviews. Finally, the feasibility of the proposed method is verified by comparison with other methods.

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Data availability

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

Abbreviations

DHLTS:

Double hierarchy linguistic term set

DHHFLE:

Double hierarchy hesitant fuzzy linguistic element

DHHFLTS:

Double hierarchy hesitant fuzzy linguistic term set

PDHLTS:

Probabilistic double hierarchy linguistic term set

IP-DHLTS:

Interval probabilistic double hierarchy linguistic term set

EDAS:

Evaluation based on distance from average solution

NLP:

Natural language processing

TOPSIS:

Technique for order preference by similarity to ideal solution

VIKOR:

VIse Kriterijumska Optimizacija I Kompromisno Resenje

AV:

Average solution

PDA:

Positive distance from average

NDA:

Negative distance from average

GLDS:

Gained and lost dominance score

GDS:

Gained dominance score

LDS:

Lost dominance score

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Funding

The work was supported by the National Natural Science Foundation of China (Nos. 72071135, 71771155).

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Authors and Affiliations

  1. Business School, Sichuan University, Chengdu, 610064, China

    Xindi Wang, Zeshui Xu & Xunjie Gou

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  1. Xindi Wang
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  2. Zeshui Xu
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  3. Xunjie Gou
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by author Xindi Wang, author Xunjie Gou and author Zeshui Xu. The first draft of the manuscript was written by author Xindi Wang and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Zeshui Xu.

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Wang, X., Xu, Z. & Gou, X. The Interval probabilistic double hierarchy linguistic EDAS method based on natural language processing basic techniques and its application to hotel online reviews. Int. J. Mach. Learn. & Cyber. 13, 1517–1534 (2022). https://doi.org/10.1007/s13042-021-01463-w

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