LikeSNU 서울대학교 도서관
SNU Big Data Knowledge Information Platform

Full Menu

AI
Report registration
  • Type
  • Title
  • Group
  • Link
  • Thumbnail
Paper List
Paper List (0Count) Export to Excel

There is no data.

민원 분석을 위한 텍스트 마이닝 기법 연구: 계층적 연관성 분석

Author
김현종, 이태헌, 유승의, 김나랑
Journal Title
한국산업정보학회논문지
Publication Year
2018
Summary

This study improved text mining techniques for complaint data analysis to accurately derive citizen requirements and proposed a hierarchical association analysis method. Based on the principle of the Co-Occurrences Structure Map, the analysis was structured around core subject words and first- and second-order related words, utilizing Busan City complaint data to overcome the limitations of existing association analysis and more accurately identify citizen requirements.

Quotation Papers(0)

List of papers cited by this paper

Thesis Indicator

Related Content

LikeSNU analyzes your query semantically to recommend related resources.

Previous
Next

인천은 무엇을 원하는가: 국민 신문고 민원 데이터를 활용한 시민 의견 분석

이준호, 김청택 · 2021

도시연구

Analysis of public complaints to identify priority policy areas: Evidence from a Satellite City around Seoul

Lee E.,Lee S.,Kim K.S.,Pham V.H.,Sul J. · 2019

Sustainability (Switzerland)

거주민 공간복지 향상을 위한 공공 개방 민원 데이터 분석 모델 - 강동구 공간복지 분석 사례를 중심으로 - A Public Open Civil Complaint Data Analysis Model to Improve Spatial Welfare for Residents - A Case Study of Community Welfare Analysis in Gangdong District -

신동윤 · 2023

KIBIM Magazine

Previous
Next
TOP