Recommendation decision-making algorithm for sharing accommodation using probabilistic hesitant fuzzy sets and bipartite network projection

In recent years, with the uninterrupted development of sharing accommodation, it not only caters to the diversified accommodation of tourists, but also takes an active role in expanding employment and entrepreneurship channels, enhancing the income of urban and rural residents, and promoting the rev...

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Bibliographic Details
Published in:Complex & intelligent systems 2020-07, Vol.6 (2), p.431-445
Main Authors: Cao, Qian, Liu, Xiaodi, Wang, Zengwen, Zhang, Shitao, Wu, Jian
Format: Article
Language:English
Subjects:
Accommodation
Algorithms
Complexity
Computational Intelligence
Data Structures and Information Theory
Decision making
Engineering
Fuzzy sets
Graph theory
Original Article
Rural areas
Urban regeneration
User satisfaction
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Summary:In recent years, with the uninterrupted development of sharing accommodation, it not only caters to the diversified accommodation of tourists, but also takes an active role in expanding employment and entrepreneurship channels, enhancing the income of urban and rural residents, and promoting the revitalization of rural areas. However, with the continuous expansion of the scale of sharing accommodation, it is fairly complicated for users to search appropriate services or information. The decision-making problems become more and more complicated. Hence, a probabilistic hesitant fuzzy recommendation decision-making algorithm based on bipartite network projection is proposed in this paper. First of all, combining the users’ decision-making information and the experts’ evaluation information, a bipartite graph connecting users and alternatives is established. Then, the satisfaction degree of probabilistic hesitant fuzzy element is defined. Besides, the recommended alternative is obtained by the allocation of resources. Finally, a numerical case of Airbnb users is given to illustrate the feasibility and effectiveness of the proposed method.
ISSN:2199-4536
2198-6053
DOI:10.1007/s40747-020-00142-7