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

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.