• Title/Summary/Keyword: Civil Complaint

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Korean Text Classification Using Randomforest and XGBoost Focusing on Seoul Metropolitan Civil Complaint Data (RandomForest와 XGBoost를 활용한 한국어 텍스트 분류: 서울특별시 응답소 민원 데이터를 중심으로)

  • Ha, Ji-Eun;Shin, Hyun-Chul;Lee, Zoon-Ky
    • 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.

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Measuring the Public Service Quality Using Process Mining: Focusing on N City's Building Licensing Complaint Service (프로세스 마이닝을 이용한 공공서비스의 품질 측정: N시의 건축 인허가 민원 서비스를 중심으로)

  • Lee, Jung Seung
    • Journal of Intelligence and Information Systems
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    • v.25 no.4
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    • pp.35-52
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    • 2019
  • As public services are provided in various forms, including e-government, the level of public demand for public service quality is increasing. Although continuous measurement and improvement of the quality of public services is needed to improve the quality of public services, traditional surveys are costly and time-consuming and have limitations. Therefore, there is a need for an analytical technique that can measure the quality of public services quickly and accurately at any time based on the data generated from public services. In this study, we analyzed the quality of public services based on data using process mining techniques for civil licensing services in N city. It is because the N city's building license complaint service can secure data necessary for analysis and can be spread to other institutions through public service quality management. This study conducted process mining on a total of 3678 building license complaint services in N city for two years from January 2014, and identified process maps and departments with high frequency and long processing time. According to the analysis results, there was a case where a department was crowded or relatively few at a certain point in time. In addition, there was a reasonable doubt that the increase in the number of complaints would increase the time required to complete the complaints. According to the analysis results, the time required to complete the complaint was varied from the same day to a year and 146 days. The cumulative frequency of the top four departments of the Sewage Treatment Division, the Waterworks Division, the Urban Design Division, and the Green Growth Division exceeded 50% and the cumulative frequency of the top nine departments exceeded 70%. Higher departments were limited and there was a great deal of unbalanced load among departments. Most complaint services have a variety of different patterns of processes. Research shows that the number of 'complementary' decisions has the greatest impact on the length of a complaint. This is interpreted as a lengthy period until the completion of the entire complaint is required because the 'complement' decision requires a physical period in which the complainant supplements and submits the documents again. In order to solve these problems, it is possible to drastically reduce the overall processing time of the complaints by preparing thoroughly before the filing of the complaints or in the preparation of the complaints, or the 'complementary' decision of other complaints. By clarifying and disclosing the cause and solution of one of the important data in the system, it helps the complainant to prepare in advance and convinces that the documents prepared by the public information will be passed. The transparency of complaints can be sufficiently predictable. Documents prepared by pre-disclosed information are likely to be processed without problems, which not only shortens the processing period but also improves work efficiency by eliminating the need for renegotiation or multiple tasks from the point of view of the processor. The results of this study can be used to find departments with high burdens of civil complaints at certain points of time and to flexibly manage the workforce allocation between departments. In addition, as a result of analyzing the pattern of the departments participating in the consultation by the characteristics of the complaints, it is possible to use it for automation or recommendation when requesting the consultation department. In addition, by using various data generated during the complaint process and using machine learning techniques, the pattern of the complaint process can be found. It can be used for automation / intelligence of civil complaint processing by making this algorithm and applying it to the system. This study is expected to be used to suggest future public service quality improvement through process mining analysis on civil service.

Rock Crushing and Gel Crushing of Ocean Traffic Facilities Foundation (해양교통시설기초 암반파쇄와 겔파쇄)

  • Lee, Soo-Gwan
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2009.06a
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    • pp.419-424
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    • 2009
  • The ocean rock was crushed mainly by drop hammer and blasting. In recent years, because of farming and harbors extension, the ocean rock crushing method is changing to popular complaint solving type. Effective rock crushing methods of protecting environment are studied under consideration for topography, farming, structures, electronic equipment, environment protection arm near to rock crushing sector. Effective rock crushing methods are compared under consideration for crushing volume, rock quality, distribution, crushing speed. Effective rock crushing methods at once solving popular complaint and protecting ocean environment and building ocean structures, are compared according to the coast development.

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Odor Classification and Source Analysis using Pseudo Inverse (Pseudo Inverse를 이용한 악취분류와 악취원 분석)

  • Yu, Suk-Hyun;Park, Sang-Jin;Koo, Youn-Seo;Kwon, Hee-Yong
    • Journal of Korea Multimedia Society
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    • v.13 no.8
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    • pp.1171-1182
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    • 2010
  • In this paper, odor classification and source analysis methods are proposed to trace odor sources in th air at the specific place and period. It is necessary to generate representative patterns in order to classify the various odors efficiently. We, therefore, create 67 kinds of odor representative patterns measured from the main sources. considering the air mixed with various odors, several mixed representative patterns for odor sources are generated with the combination of two or three different odors. In addition, the weight of odor sources for an odor from a civil complaint region are computed using pseudo inverse method. As a result, we can trace and identify the odor sources to lead to a specific odor and the contribution of each source. The results of this study will be useful for settling the civil complaint related with odors.

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

  • Shin, Dongyoun
    • Journal of KIBIM
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    • v.13 no.3
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    • pp.39-47
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    • 2023
  • This study aims to introduce a model for enhancing community well-being through the utilization of public open data. To objectively assess abstract notions of residential satisfaction, text data from complaints is analyzed. By leveraging accessible public data, costs related to data collection are minimized. Initially, relevant text data containing civic complaints is collected and refined by removing extraneous information. This processed data is then combined with meaningful datasets and subjected to topic modeling, a text mining technique. The insights derived are visualized using Geographic Information System (GIS) and Application Programming Interface (API) data. The efficacy of this analytical model was demonstrated in the Godeok/Gangil area. The proposed methodology allows for comprehensive analysis across time, space, and categories. This flexible approach involves incorporating specific public open data as needed, all within the overarching framework.

Analysis of Urban Environmental Factors Affecting Illegal Parking: Focused on the Smart Civil Complaints Data in Seoul, Korea (불법 주정차에 영향을 미치는 도시 환경 요인 분석: 서울시 스마트 불편신고 민원자료를 중심으로)

  • Park, Junsang;Lee, Sugie
    • Journal of the Korean Regional Science Association
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    • v.38 no.3
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    • pp.3-17
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    • 2022
  • The automobile-centered lifestyle has provided many advantages to urban residents, but it is also causing various problems. Among them, illegal parking is one of the representative urban problems that negatively affect them. The purpose of this study is to derive the urban environmental factors affecting illegal parking and provide policy implications by using data related to illegal parking among civil complaints about smart inconvenience reports in Seoul in 2019. It was judged that the influencing factors would differ depending on the time of the complaint, and the analysis was conducted by dividing the time of the complaint into a whole day, daytime, and nighttime. As a result of the analysis of this study, it was found that land-use variables and the number of POI facilities were closely related to illegal parking complaints. Also, the subway station area and road width were found to be closely related to illegal parking complaints. On the other hand, parking facilities did not show significant results with illegal parking complaints. This study showed that the use of civic complaint data could be used as important data to identify urban problems that city residents actually experience and to come up with policy implications.

A Study on Text Mining Methods to Analyze Civil Complaints: Structured Association Analysis (민원 분석을 위한 텍스트 마이닝 기법 연구: 계층적 연관성 분석)

  • Kim, HyunJong;Lee, TaiHun;Ryu, SeungEui;Kim, NaRang
    • Journal of Korea Society of Industrial Information Systems
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    • v.23 no.3
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    • pp.13-24
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    • 2018
  • For government and public institutions, civil complaints containing direct requirements of citizens can be utilized as important data in developing policies. However, it is difficult to draw accurate requirements using text mining methods since the nature of the complaint text is unstructured. In this study, a new method is proposed that draws the exact requirements of citizens, improving the previous text mining in analyzing the data of civil complaints. The new text-mining method is based on the principle of Co-Occurrences Structure Map, and it is structured by two-step association analysis, so that it consists of the first-order related word and a second-order related word based on the core subject word. For the analysis, 3,004 cases posted on the electronic bulletin board of Busan City for the year 2016 are used. This study's academic contribution suggests a method deriving the requirements of citizens from the civil affairs data. As a practical contribution, it also enables policy development using civil service data.

A Text Mining Study on Endangered Wildlife Complaints - Discovery of Key Issues through LDA Topic Modeling and Network Analysis - (멸종위기 야생생물 민원 텍스트 마이닝 연구 - LDA 토픽 모델링과 네트워크 분석을 통한 주요 이슈 발굴 -)

  • Kim, Na-Yeong;Nam, Hee-Jung;Park, Yong-Su
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.26 no.6
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    • pp.205-220
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    • 2023
  • This study aimed to analyze the needs and interests of the public on endangered wildlife using complaint big data. We collected 1,203 complaints and their corresponding text data on endangered wildlife, pre-processed them, and constructed a document-term matrix for 1,739 text data. We performed LDA (Latent Dirichlet Allocation) topic modeling and network analysis. The results revealed that the complaints on endangered wildlife peaked in June-August, and the interest shifted from insects to various endangered wildlife in the living area, such as mammals, birds, and amphibians. In addition, the complaints on endangered wildlife could be categorized into 8 topics and 5 clusters, such as discovery report, habitat protection and response request, information inquiry, investigation and action request, and consultation request. The co-occurrence network analysis for each topic showed that the keywords reflecting the call center reporting procedure, such as photo, send, and take, had high centrality in common, and other keywords such as dung beetle, know, absence and think played an important role in the network. Through this analysis, we identified the main keywords and their relationships within each topic and derived the main issues for each topic. This study confirmed the increasing and diversifying public interest and complaints on endangered wildlife and highlighted the need for professional response. We also suggested developing and extending participatory conservation plans that align with the public's preferences and demands. This study demonstrated the feasibility of using complaint big data on endangered wildlife and its implications for policy decision-making and public promotion on endangered wildlife.

A Study on the model of CCTV Image Information Integration portal (CCTV 영상자료 통합포털 구축 모델에 관한 연구)

  • Kang, Poo-Reum;Kim, Kui-Nam J.
    • Convergence Security Journal
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    • v.12 no.2
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    • pp.43-51
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    • 2012
  • CCTV would be the effective way in the prevention of abuse, as well as recorded image information evidence of the crime as a significant legal effect. But recorded image information As evidence by utilizing the Complaint/complaint handling, and administrative business processes that are currently operating offline procedural complexity and unnecessary time appear costly, privacy remains an issue to be solved, etc. Runoff. In this paper, incidence rate of offline business processing phase to solve the problems proposed to build unified portal for CCTV image information and the existing studies on the effectiveness of electronic civil service system, previous studies by analyzing e-government in accordance with laws and privacy laws, CCTV image information portal deployment model is applied to data integration occurs are trying to solve the problem effectively.

A Study on the Visualization of Geospatial Big Data using Sentiment Analysis of Collective Civil Complaints (집단민원의 감성분석을 이용한 공간빅데이터 시각화 방안)

  • Yong-Jin JOO
    • Journal of the Korean Association of Geographic Information Studies
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    • v.26 no.1
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    • pp.11-20
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    • 2023
  • Traditionally, surveys or interview studies have been used to measure satisfaction factors for public services. This method focuses on the simple frequency of civil complaints and does not consider the aggravation of emotions implied in civil complaints. As a result, it is difficult to judge the urgency of civil complaints and the severity of grievances experienced by civil petitioners. This study aims to calculate the negative emotional value of collective complaints by using the happiness score for each word on the Hedonometer. The Anti-Corruption and Civil Rights Commission applied a Hedonometer to the top civil complaint topics and related keyword data by region in 2021 to calculate negative sentiment values by subject of civil complaints, and visualize the distribution by region. Using the negative emotional values derived from the results of this study, the severity of emotions contained in civil complaints can be considered. It is also expected to be helpful in determining the urgency of civil complaints and the severity of grievances experienced by civil petitioners.