• Korean Journal of Construction Engineering and Management
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• v.19 no.1
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• pp.12-20
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• 2018

Construction projects are often large in magnitude and high in construction amount. Therefore, construction activities have great impacts on business economics and social lives in the surrounding regional area. The residents can have public grievances if they are badly affected by the construction activities. Project owners should try to minimize adverse impacts in planning and design as well as in construction. The objective of this paper is to establish a public grievance breakdown structure and apply this breakdown structure to improving design functions in an effort to minimize public grievances. This research has been done in three steps of 1) analyzing the characteristics of public grievances in construction projects; 2) developing a public grievance breakdown structure; and 3) based on the public grievance breakdown structure, generating design alternatives that can improve the preparedness against public grievances. A case study has been done to demonstrate the applicability of the public grievance breakdown structure in generating design alternatives to minimize public grievances.

• Proceedings of the Korea Contents Association Conference
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• 2015.05a
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• pp.453-454
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• 2015

본 논문에서는 공공 민원 빅데이터 분석을 통하여 민원추이 분석을 하고, 민원 추이 분석을 통하여 민원 통계 분석 서비스, 민원 분류 분석 서비스, 민원 정책(이슈) 분석 서비스에 대한 가시화 서비스 기능을 제안한다.

• The Journal of Bigdata
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• v.2 no.2
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• pp.95-104
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• 2017

In 2014, Seoul Metropolitan Government launched a response service aimed at responding promptly to civil complaints. The complaints received are categorized based on their content and sent to the department in charge. If this part can be automated, the time and labor costs will be reduced. In this study, we collected 17,700 cases of complaints for 7 years from June 1, 2010 to May 31, 2017. We compared the XGBoost with RandomForest and confirmed the suitability of Korean text classification. As a result, the accuracy of XGBoost compared to RandomForest is generally high. The accuracy of RandomForest was unstable after upsampling and downsampling using the same sample, while XGBoost showed stable overall accuracy.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.135-144
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• 2024

In this study, we propose an automatic classification model for quantitative multidimensional analysis based on facet theory to understand public opinions and demands on major issues through big data analysis. Civil complaints, as a form of public feedback, are generated by various individuals on multiple topics repeatedly and continuously in real-time, which can be challenging for officials to read and analyze efficiently. Specifically, our research introduces a new classification framework that utilizes facet theory and political analysis models to analyze the characteristics of citizen complaints and apply them to the policy-making process. Furthermore, to reduce administrative tasks related to complaint analysis and processing and to facilitate citizen policy participation, we employ deep learning to automatically extract and classify attributes based on the facet analysis framework. The results of this study are expected to provide important insights into understanding and analyzing the characteristics of big data related to citizen complaints, which can pave the way for future research in various fields beyond the public sector, such as education, industry, and healthcare, for quantifying unstructured data and utilizing multidimensional analysis. In practical terms, improving the processing system for large-scale electronic complaints and automation through deep learning can enhance the efficiency and responsiveness of complaint handling, and this approach can also be applied to text data processing in other fields.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.259-263
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• 2006

Civil appeals under constructions cause a lot of difficulties of doing construction because of compensations, interruption of works, administrative punishments, etc. So this research focused on the characteristics of civil complaints against constructions by analyzing the causes of civil appeals and treatment conditions classified by year, geography, and breaking time. This research indicates three points. (l) As the level of civil life and consciousness is increased, the number of civil appeals against constructions are tending upwards in view of the results so far achieved by year. (2) Analysis about civil appeals classified by geography shows that the rate of civil affairs in Gang-nam District are higher than that of others.(3) 96% of the civil appeals by breaking time are occurred under the constructions. By predicting and treating of what type of civil appeals are occurred, this research can be used as data which make damage minimized.

• Proceedings of the Korean Society for Information Management Conference
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• 2013.08a
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• pp.175-178
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• 2013

웹의 발달과 전자정부의 지향으로, 행정기관의 웹사이트를 통한 민원처리가 증가하고 있다. 게시판을 통해 이용자가 민원을 제기하면, 각 기관에서는 담당자를 배정해 처리하지만 해당 게시물을 공기록으로 보존하지는 않는다. 공공사이트를 통한 투명한 행정을 위해서는 게시물도 공기록물로 보존하는 체계가 마련될 필요가 있다. 이를 위해, 정부기능연계모델(BRM)을 기준으로, 공공사이트의 게시글을 자동으로 분류하는 시스템을 구현하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1405-1408
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• 2011

도로의 일부구역을 일반시민이 특정목적으로 사용하기 위한 도로점용허가는 국민생활 및 재산권과 밀접한 관계가 있으나 설계도 등 구비서류가 다양하고 복잡하여 민원인이 신청하기에 불편하고, 이는 곧 민원행정에 대한 국민 신뢰도 저하로 이어지고 있다. 도로점용허가는 서류가 대부분 종이로 제출되어 보관 및 자료찾기 등 사후관리가 어렵고 민원 대응 등 업무처리가 힘들어 행정효율성 저하를 초래하고 있다. 본 연구는 도로점용허가 전반을 지원할 수 있는 온라인시스템(이하 '도로점용시스템'이라함)을 구축하기 위한 정보분류체계를 개발하여 대국민 서비스 및 업무효율성 향상을 도모하고자 한다.

• 한국IT서비스학회:학술대회논문집
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• 2009.11a
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• pp.264-269
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• 2009

본 연구에서는 IPTV를 이용한 전자정부 민원 서비스를 제공하기 위한 서비스 제공 로드맵 수립과 관련 기술들을 조사 하였다. 이를 위해 국내외 로드맵 수립 관련 연구들을 정리하고 IPTV를 기반으로 전자민원 서비스를 제공하기 위한 로드맵 수립 방안을 제시 하였다. 또한 IPTV기반으로 제공하고자 하는 전자민원서비스를 이용빈도와 복잡성에 따라서 정보제공형, 상호작용형, 거래처리형으로 분류하고, 각서비스 유형별로 필요한 기술들을 제시 하였다. 이를 기반으로 전자정부 서비스를 IPTV기반으로 제공하기 위한 서비스 로드맵을 도출하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.3
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• pp.319-327
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• 2016

Korea faces a wide range of problems in areas such as safety, environment, and traffic due to the rapid economic development and urbanization process. Despite the local governments’ efforts to deal with electronic civil complaints and solve urban problems, civil complaints have been on the increase year by year. In this study, we collected civil complaint data over the last six years from a small and medium-sized city, Jinju-si. In order to conduct a spatial distribution pattern analysis, we indicated the location data on the area through Geocoding after classifying the reasons for civil complaints and then extracted the location data of the civil complaint occurrence spots in order to analyze the correlation between electronic civil complaints and land use. Results demonstrated that electronic civil complaints in Jinju-si were clustered in residential, central commercial, and residential-industrial mixed-use areas—areas where land development had been completed within the city center. After analyzing the civil complaints according to the land use, results revealed that complaints about illegal parking were the highest. Regarding the analysis results of facility distribution within a 50m radius from the civil complaint areas, civil complaints occurred a lot in detached housing areas located within the commercial and residential-industrial mixed-use areas. In the case of residential areas(old downtown), civil complaints were condensed in the areas with many ordinary restaurants. This research explored civil complaints in terms of the urban space and can be expected to be effectively utilized in finding solutions to the civil complaints

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.5-14
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• 2017

Korea, which has undergone a rapid urbanization, faces various problems such as the management of facilities, safety, environment and transportation. To solve civil complaints, local governments receive electronic complaints, but complaints are increasing. Therefore, this study conducted the spatial distribution pattern analysis and the trend analysis by presenting location data on spatial information through Geo-coding by collecting electronic civil petition data over the last 10 years targeting Jinju city. Using the ARIMA model, this study predicted the occurrence of complaints over the next two years (2016~2017) through a time series forecast analysis. As a result, the complaints related to illegal parking were the highest, the complaint related to noise was the second highest, and the complaints related to illegal garbage dumping was the third highest. In addition, the analysis of the spatial distribution pattern shows that the largest hot spot was formed in the central commercial district every year. As a result of the time series forecasting analysis for the crackdown of the illegal parking, complaints increased slightly. To compare the predicted value and the actual data showed a similar pattern. It is judged that this study will be utilized to establish effective countermeasures against civil complaints.