Spatial Co-Location Pattern Mining Based on Hesitant Fuzzy Location
Authors: 
Minhui Huang, Bo Wei, Zhaowei LiuAuthors Info & Claims
Minhui Huang, Bo Wei, Zhaowei LiuAuthors Info & ClaimsPages 472 - 476
Abstract
Spatial Co-location pattern mining is an important research content of data mining. Traditional spatial co-location pattern mining and those based on fuzzy sets can only deal with certain data and uncertain data expressed by a fuzzy membership degree, which the data that there are many possible values of fuzzy membership degree cannot be processed. To this, combined with the theory and method of hesitant fuzzy sets, a method of spatial co-location pattern mining based on hesitant fuzzy location is proposed, which the hesitant fuzzy location of spatial feature instances is defined by using the characteristic that hesitant fuzzy sets can express multiple possible fuzzy membership degrees at the same time. Hesitation fuzzy score space proximity is defined by score function of hesitant fuzzy sets, and then the participation ratio and participation index of hesitant fuzzy location are defined by combined with the hesitant fuzzy location and hesitant fuzzy score function. The algorithm flow of the proposed method is given. The experimental results show that the proposed method is effective and it can find more frequent spatial co-location patterns compared with the existing method.
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Index Terms
- Spatial Co-Location Pattern Mining Based on Hesitant Fuzzy Location
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Published In
December 2020
687 pages
ISBN:9781450388665
DOI:10.1145/3452940
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Association for Computing Machinery
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Publication History
Published: 17 May 2021
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- Research-article
- Research
- Refereed limited
Funding Sources
- ?BaGui Scholars? Special Funds of Guangxi Province
- Foundation of Guangxi Key Laboratory of Spatial Information and Geomatics
- National Natural Science Foundation of China
- Natural Science Foundation of Guangxi Province
- Doctoral Foundation of Guilin University of Technology
Conference
ICITEE2020
ICITEE2020: The 3rd International Conference on Information Technologies and Electrical Engineering
December 3 - 5, 2020
Hunan, Changde City, China
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