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빅데이터를 활용한 가구특성별 주거입지 및 주택유형 선택에 관한 데이터베이스 구축Construction of database about Residential location based on household characteristics and selection of houses-type utilizing Big Data

Other Titles
Construction of database about Residential location based on household characteristics and selection of houses-type utilizing Big Data
Authors
백민호오대식전한종
Issue Date
Feb-2015
Publisher
한국CAD/CAM학회
Keywords
Residential location; Housing type; Big data; Data base; Statistical analysis
Citation
Korean Journal of Computational Design and Engineering, pp 202 - 207
Pages
6
Indexed
DOMESTIC
Journal Title
Korean Journal of Computational Design and Engineering
Start Page
202
End Page
207
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/157843
ISSN
1226-0606
Abstract
Recently there has been a growing interest in the effective use of big data. In particular, until now extracts the rules and patterns from a large amount of various data that little-known, is growing social interest to use the information. Big data is simply to extract information that is not limited to extract not well known information by monitoring the social issues but develop customized service model through the simulation, formulates support services, and a policy can be the ultimate purpose is to cooperate to achieve a happy society. However,the reality is still that such as academic research and discussion for effective use of big data from residential, urban, architecture in the social sciences. In this study, as part of the effective use of big data and take advantage of government 3.0 public data that the current government is promoting, based on the database to select the type of furniture properties by residential location and housing type, it is an object of this by indexing to construct a data rule. In this study, it is Summarizing to the public data Obtain meaningful result value. It plans to leverage the data subsystem for establishing decision support systems needed for decision-making on household characteristics by residential location and housing type selected.
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