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DBpiaIn this study, web document frequency of city place name is analyzed and it is used as the dataset for rank-size analysis. The search keywords are compared in the context of spatial meaning and the different domain corpus is applied. The acquired sear...
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https://www.riss.kr/link?id=A100142181
- 저자
- 발행기관
- 학술지명
- 권호사항
-
발행연도
2007
-
작성언어
Korean
-
주제어
문서빈도 ; 웹 마이닝 ; 도시규모분포 ; 지프의 법칙 ; Document Frequency ; Web Mining ; Rank-Size Rule ; Zipf`s Law
-
KDC
981
-
등재정보
KCI등재
-
자료형태
학술저널
- 발행기관 URL
-
수록면
290-300(11쪽)
- 제공처
-
0
상세조회 -
0
다운로드
부가정보
다국어 초록 (Multilingual Abstract)
In this study, web document frequency of city place name is analyzed and it is used as the dataset for rank-size analysis. The search keywords are compared in the context of spatial meaning and the different domain corpus is applied. The acquired search results are applied for the further analysis. Firstly, the rank-size analysis is applied to compare the result between population and document frequency. Secondly, in case of correlation analysis, the significant changes are revealed when the spatial criteria for search keywords are increased. In case of corpus, COM, NET, and ORG shows the higher coefficient values. Lastly, the cluster analysis is applied to classify the list of cities that shows the similarity and difference. These analyses have a significant role in representing the rank-size distribution of city names that are reflected on the web documents in the information society.
In this study, web document frequency of city place name is analyzed and it is used as the dataset for rank-size analysis. The search keywords are compared in the context of spatial meaning and the different domain corpus is applied. The acquired search results are applied for the further analysis. Firstly, the rank-size analysis is applied to compare the result between population and document frequency. Secondly, in case of correlation analysis, the significant changes are revealed when the spatial criteria for search keywords are increased. In case of corpus, COM, NET, and ORG shows the higher coefficient values. Lastly, the cluster analysis is applied to classify the list of cities that shows the similarity and difference. These analyses have a significant role in representing the rank-size distribution of city names that are reflected on the web documents in the information society.
동일학술지(권/호) 다른 논문
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