Fuzzy geo-processing for characterization of social groups: an application to a Brazilian mid-size city

Autor:	J. A. Silva, G. R. A. Gonzalez, A. G. Evsukoff, A. P. B. Sobral, R. C. Pinto
Rok vydání:	2006
Předmět:	Fuzzy classification Computer science business.industry City map Distribution (economics) Space (commercial competition) computer.software_genre Fuzzy logic Social group Revenue Data mining Cluster analysis business computer
Zdroj:	Data Mining VII: Data, Text and Web Mining and their Business Applications.
ISSN:	1743-3517 1746-4463
Popis:	This paper presents a method for the spatial representation of social-economic groups. This work is based on the Brazilian census geo-referenced data for the revenue and education level of 540 districts in a mid-size city. The data was analyzed by k-means clustering algorithms for determination of groups of similar behavior based only on the revenue and education level data. The groups were then plotted into the city map using geo-referenced information. The aim of this study is to analyze the spatial distribution of groups of equivalent socio-economic levels, taking into account the uncertainty of the classification process. The results show that the model is able to represent the distribution of the social groups in an inter-related and continuous space.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a2269ae934c217fd768d042853081092 https://doi.org/10.2495/data060051 Zobrazit plný text záznamu