In:
International Transactions in Operational Research, Wiley, Vol. 27, No. 3 ( 2020-05), p. 1526-1549
Abstract:
A fuzzy clustering method with linguistic information is introduced. It uses a minimizing cross‐entropy model to avoid setting the clustering threshold artificially. During the clustering, the semantics of the linguistic information is conservatively represented by solving a programming. It maximizes the potential differences between the objects to be clustered, and further helps an analyst to reach a semantics‐robust clustering result. A case study on clustering a sample destination set, which includes 13 Asia Pacific regions, based on a group of tourists’ perceptions is also proposed.
Type of Medium:
Online Resource
ISSN:
0969-6016
,
1475-3995
Language:
English
Publisher:
Wiley
Publication Date:
2020
detail.hit.zdb_id:
2019815-2
SSG:
3,2
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