• 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.

• Journal of Korean Society of Environmental Engineers
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• v.37 no.4
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• pp.240-245
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• 2015

This study aimed to provide the basic data to establish measures for the management of the public toilets and reduction of the offensive odor through the air dilution olfactory method and instrumental analysis about offensive odor dilution rate of public toilets, focusing on the Dong-gu, Daejeon Metropolitan City, Korea. The offensive odor intensities ranged from 10 degree to 669 degrees in the urinal toilets and from 31 to 464 in closet bowl toilets. Meanwhile, toilets that had offensive odor of more than 2.5, of which a civil complaint can be filed, were researched 6 (33%). Offensive odor intensities were different according to the closet bowl toilets of the flush, fermented and conventional methods and the year of their installation, but not according to the area of the toilets. As a result of the instrumental analysis targeting 6 public toilets to identify the offensive odor substance, the maximal concentration of $NH_3$ was 2.04 ppm and the average concentration was 0.67 ppm, but $H_2S$, $CH_3SH$ and $(CH_3)_3N$ were not detected. In the fermented and conventional public toilets were not soaps, air fresheners and wastebaskets. Just 50% of the flush toilets had toilet tissue.

• 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.

• Fashion & Textile Research Journal
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• v.12 no.6
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• pp.745-754
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• 2010

This study is to find return factors when modern consumers purchase goods from an internet shopping mall and then to analyze the characteristics of complaints act and information search behavior. Subjects of research are 245 men and women, who have experience with more than one return in internet fashion shopping mall, in their twenties. The data were analyzed by using Factor analysis, Cronbach's analysis, one-way ANOVA, Duncan test as a post identification, Pearson's correlation analysis and multiple regression analysis. The results of this study are that male and female consumers in their 20s are mainly aware of the return factors: impulse buying, product status, deliver service, service after purchase, hype and comfortableness. And complains behavior often conduct public action, private action, nonaction. Information search behaviors for risk reduction when they purchase are product comparison, oral information search, neutral marketing information search, and service information search. The return factor from the internet fashion shopping had the greatest impact on public action and deliver services factor was a big complaint. In addition, impulse buying & Hype affect private action and non-action is influenced by impulse purchase. The consumer types by the return factors in internet fashion shopping mall are classified into the return group by deliver service, the return group by complex factors, and the return group by product status. Furthermore, there are significant differences in complaining behavior among these groups. In the information search behavior for reduction of risk factors, the return group by complex factors did more active information search behavior than the other groups. The return group by deliver service searched oral information and the return group by product status explored the neutral marketing information.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.272-282
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• 2022

Between 2014 and 2019, the US lost more than 2.1 billion USD to phishing attacks, according to the FBI's Internet Crime Complaint Center, and COVID-19 scam complaints totaled more than 1,200. Phishing attacks reflect these awful effects. Phishing websites (PWs) detection appear in the literature. Previous methods included maintaining a centralized blacklist that is manually updated, but newly created pseudonyms cannot be detected. Several recent studies utilized supervised machine learning (SML) algorithms and schemes to manipulate the PWs detection problem. URL extraction-based algorithms and schemes. These studies demonstrate that some classification algorithms are more effective on different data sets. However, for the phishing site detection problem, no widely known classifier has been developed. This study is aimed at identifying the features and schemes of SML that work best in the face of PWs across all publicly available phishing data sets. The Scikit Learn library has eight widely used classification algorithms configured for assessment on the public phishing datasets. Eight was tested. Later, classification algorithms were used to measure accuracy on three different datasets for statistically significant differences, along with the Welch t-test. Assemblies and neural networks outclass classical algorithms in this study. On three publicly accessible phishing datasets, eight traditional SML algorithms were evaluated, and the results were calculated in terms of classification accuracy and classifier ranking as shown in tables 4 and 8. Eventually, on severely unbalanced datasets, classifiers that obtained higher than 99.0 percent classification accuracy. Finally, the results show that this could also be adapted and outperforms conventional techniques with good precision.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.6
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• pp.651-659
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• 2014

With the popularization of big data environment, big data have been highlighted as a key information strategy to establish national spatial data infrastructure for a scientific land policy and the extension of the creative economy. Especially interesting from our point of view is the cadastral information is a core national information source that forms the basis of spatial information that leads to people's daily life including the production and consumption of information related to real estate. The purpose of our paper is to suggest the scheme of big data analytics with respect to the articles of cadastral resurvey project in order to approach cadastral information in terms of spatial data integration. As specific research method, the TM (Text Mining) package from R was used to read various formats of news reports as texts, and nouns were extracted by using the KoNLP package. That is, we searched the main keywords regarding cadastral resurvey, performing extraction of compound noun and data mining analysis. And visualization of the results was presented. In addition, new reports related to cadastral resurvey between 2012 and 2014 were searched in newspapers, and nouns were extracted from the searched data for the data mining analysis of cadastral information. Furthermore, the approval rating, reliability, and improvement of rules were presented through correlation analyses among the extracted compound nouns. As a result of the correlation analysis among the most frequently used ones of the extracted nouns, five groups of data consisting of 133 keywords were generated. The most frequently appeared words were "cadastral resurvey," "civil complaint," "dispute," "cadastral survey," "lawsuit," "settlement," "mediation," "discrepant land," and "parcel." In Conclusions, the cadastral resurvey performed in some local governments has been proceeding smoothly as positive results. On the other hands, disputes from owner of land have been provoking a stream of complaints from parcel surveying for the cadastral resurvey. Through such keyword analysis, various public opinion and the types of civil complaints related to the cadastral resurvey project can be identified to prevent them through pre-emptive responses for direct call centre on the cadastral surveying, Electronic civil service and customer counseling, and high quality services about cadastral information can be provided. This study, therefore, provides a stepping stones for developing an account of big data analytics which is able to comprehensively examine and visualize a variety of news report and opinions in cadastral resurvey project promotion. Henceforth, this will contribute to establish the foundation for a framework of the information utilization, enabling scientific decision making with speediness and correctness.

• Journal of Preventive Medicine and Public Health
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• v.33 no.2
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• pp.184-192
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• 2000

Objectives : To inquire the prevalence and the risk factors for myofascial pain syndrome (MPS) on young boys in order to use these results as the fundamental data for the prevention of their MPS. Methods : For 7 days in May 1999, this research was taken on 489 male students ranging from 6th to 12th grade. We randomly selected a class for every group and from these classes we operated physical examinations, self-reported questionnaires and from a rehabilitation doctor, MPS test was taken. Thoracic kyphosis and lumbar lordosis were also taken by using the inclinometer. We defined MPS as a regional pain complaint, palpable taut band that is painful on compression. Results : The shoulder MPS prevalence of the subjects were 29.7 persons/100 persons. The statistics revealed that as grades went up, the percentage significantly increased in the MPS prevalence. As of case-control study, 145 students who were tested postive in all aspects were placed as cases, and 176 students who were perfectly normal as controls on risk factors. As a result of comparing the student groups who were stisfied with their chairs to the student groups were not satisfied, the taller showed a significantly higher odds ratio (p<0.01). By the multiple logistic regression test, we concluded that the MPS disease was prevailed far more in the students in the higher grades (Odds ratio: 1.16, 95% C.I.: 1.03-1.31), and also those who were dissatisfied with their chairs than in the ones who were satisfied (Odds ratio: 1.92, 95% C.I.: 1.17-3.17). Conclusions : Significant correlations showed between the MPS diagnosed group and the students who are dissatisfied with their chairs. As a result, more research and observation has to be made concerning this disease, and the desks and chairs should be adjusted to suit the student's physical standards.

• Informatization Policy
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• v.27 no.2
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• pp.66-83
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• 2020

Local issues that occur in cities typically garner great attention from the public. While local governments strive to resolve these issues, it is often difficult to effectively eliminate them all, which leads to complaints. In tackling these issues, it is imperative for local governments to use big data to identify the nature of complaints, and proactively provide solutions. This study applies the LDA topic modeling technique to research and analyze trends and patterns in complaints filed online. To this end, 9,625 cases of online complaints submitted to the city of Busan from 2015 to 2017 were analyzed, and 20 topics were identified. From these topics, key topics were singled out, and through analysis of quarterly weighting trends, four "hot" topics(Bus stops, Taxi drivers, Praises, and Administrative handling) and four "cold" topics(CCTV installation, Bus routes, Park facilities including parking, and Festivities issues) were highlighted. The study conducted big data analysis for the identification of trends and patterns in civil affairs and makes an academic impact by encouraging follow-up research. Moreover, the text mining technique used for complaint analysis can be used for other projects requiring big data processing.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.5
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• pp.78-90
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• 2013

The purpose of this study was to analyze the types and characteristics of public complaints caused by the landscape architecture projects in the case of apartment complex. Furthermore, its purpose was also to propose as the basis data for the minimization of complaints in the course of future landscape architecture projects. To analyze and categorize the apartment complex civil complaints, we collected basic and case study data from LH Corporation, SH Corporation and GICO from 2009 to 2012. We also categorized 672 landscape complaints to 73 categories and conducted a survey from residents and landscape architecture. This Survey is to use IPA can collect character(public-private), handling of civil affair(easy-hard) and analyze typical characters and difference of civil complaint awareness between landscape architecture and residents. First, we were categorized 73 civil complaints by type in 5 categories such as park, green space and street trees, pedestrian road, facilities, and others. Second, the most common landscape complaints appear in green spaces, street trees, facilities, pedestrian roads and park orders. Third, results of the analysis conducted for each item which are publicity and measures the ease. 'Facilities', 'landscape and greenery', 'pedestrian road' and others were commonly appears from residents and professional awareness of the complaints. However, complaints of park appear different awareness between landscape architecture and residents. Fourth, 35 from 73 civil complaints(47.9%) are having high publicity and easy to measure, 25 civil complaints(34.2%) has analyzed to individual and difficult to measure so about the these complaints need to check from the design step so that it is necessary to minimize the problem of additional expense by civil complaints burden and decrease the confidence of residence problem were considered.

• Journal of Korean Home Economics Education Association
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• v.22 no.3
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• pp.129-145
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• 2010

In this study, when buying fashion products through internet shopping malls, it is researched about the buying behavior, the awareness of customer review, the use and posting of customer review and the accompanying awareness. The difference of awareness on the customer review according to their involvement of clothes, are examined from high school students in Seoul. And it is examined if they experienced any dissatisfaction after their purchase and what their behavior were. The questionnaire survey was taken by 508 students from 6 high schools in Seoul. The average, the standard deviation, the frequency, the t-test, the One way ANOVA and Duncan's Multiple Test were conducted for data analysis using SPSS 17.0. In the fashion products purchase behavior of the students, The reasons of buying were mainly because of the diversity and the convenience. Some students don't shop online because screen product and actual product are not the same. The awareness of the customer review represented high in the reliability and usefulness. The awareness on the influence of the customer review represented high in the contents direction and the numbers of the customer reviews but represented low in the timeliness. As to the awareness of the customer review, the student using it represented higher in all elements such as the usefulness, the reliability, and the influence than students who not use customer review. The students posting customer review recognized higher on the usefulness and the reliability of the customer review than those who did not post it, and were highly influenced by the numbers of customer reviews. The awareness of the customer review according to the involvement of clothes was the difference only in the usefulness. As to coping actions of students experiencing dissatisfaction, the proportion of the students coping with the public action and those who do not perform any action represented high.