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- Title
Neutrosophic K-means Based Method for Handling Unlabeled Data.
- Authors
Quevedo Arnaiz, Ned Vito; Garcia Arias, Nemis; Campaña Muñoz, Leny Cecilia
- Abstract
Nowadays, incalculable volumes of data are generated due to the technological development achieved by the current society of information. The exponential growth of information significantly supports people's decision making in their daily activities. In Ecuador, there are many institutions that store the data of their processes. The tourism sector represents an example of this assertion. However, the data generated exceeds the power of analysis and processing of human beings, sometimes relevant information is presented it is not visible for persons. The present investigation proposes a solution to the described problem starting from the development of a method for the treatment of unlabeled data. The proposed method is based on the unsupervised k-means algorithm. We used rough neutrosophic sets to reduce the number of attributes. The proposal has been implemented from the stored dataset of the tourism sector in the City of Riobamba.
- Subjects
ECUADOR; TOURISM; ROUGH sets; K-means clustering; URBAN tourism; EXPONENTIAL functions
- Publication
Neutrosophic Sets & Systems, 2020, Vol 37, p308
- ISSN
2331-6055
- Publication type
Article