• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.179-196
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• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.3
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• pp.64-73
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• 2011

This study starts from the hypothesis that the information society has affected the layman's interpretation and production of content. Specifically, the manner and contents of communication concerning the landscape of Soonyoo-do Park in blogs are surveyed and the possibilities and limitations of this phenomenon are discussed. The following topics are dealt with. Firstly, what is the landscape of Seonyoodo Park as captured by bloggers? What type of landscape do bloggers respond to? Secondly, what is the unique way that bloggers capture and interpret the landscape? Thirdly, What are the possibilities and limitations discovered from the landscape as captured and interpreted by bloggers? Thus, 1,000 blog posts concerning Soonyoo-do Park, as culled from the Internet, were categorized into three areas, First are blog posts browsed by keywords such as 'photo', 'a photographer's visit', 'a good p1ace for taking photos', and 'landscape'. These are focused on the visual aspects of the landscape. The second category is posts under the keywords 'domestic travel', 'Seoul travel', 'travel', and 'recommendation'. They contain introductory information on Seonyoodo Park; that is, they focus cm the more utilitarian functions of Seonyoodo Park as a place. The third one is posts that record personal experiences. The subjects for photography are the bloggers themselves and their companions. As a result of studying the way bloggers deal with landscape, it was found that first, people have developed the ability to capture the landscape and interpret the landscape actively and independently. This process can be regarded as the reproduction of landscape and place. In addition, the recording of their appreciation and feeling overlaps with evaluation and assumption. One negative aspect, however, is that many bloggers dramatize and repeat similar scenes. This can be seen as a make-up of image. The limitations of this study include difficulty in interpretation because blogs, which are the objects of this study, are very subjective and personal. In addition, it was not easy to categorize posts because there were diverse images and a broad range of writing. Nevertheless, practitioners of landscape architecture should continue to monitor and use one-person media like blogs, because the relationship between modern man and the landscape can be better understood through them.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Child Health Nursing Research
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• v.7 no.2
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• pp.245-257
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• 2001

This study analyzed the services as operated by the Child Health Telephone Service Center. The Center is a toll free service operated as part of the community services of the Korean Academic Society of Child Health Nursing. The aim of the study was to describe the concerns of child caregivers regarding child health care as discussed during telephone counseling. Specific objectives were as follows: 1. To analyze the activities of the Center. 2. To describe the characteristics of caregivers who made phone calls for counseling services and also the characteristics of their children. 3. To analyze the content of the counseling sessions. 4. To analyze counseling content according to the characteristics of the caregivers and their children. Data used for the study were obtained from the counseling records for the period from Sept. to Dec. 1999, as kept by the three counselors at the Center. The total number of calls was 8,261 and that consisted of 15,150 questions. The total questions were merged into 13,236 by eliminating those questions which overlapped or were of similar content. The final 13,236 questions were used for the final analyses. Almost of the callers (98.4％) were mothers. Among them 89.6％ were between 25 and 35 years of age. Geographical distribution of the callers covered the whole nation. The largest numbers who made the calls were from the Seoul metropolitan area (36％), followed by 28％ from Kyung Gi Province, and 20％ were from the Kyung Sang area. Among 8,261 callers, 72.8％ were first users. Sex of the babies and children in question for counseling was about even for males and females and ages ranged from one month to six years. The largest group (62.5％) was the less than six month age group. The finalized 13,236 questions/problems were categorized into 11 problem areas. They were in order of frequency, physical problems, feedings and nutrient concerns, information on child rearing, growth and development, guidance on utilization of child care facilities, elimination problems, sleeping concerns, immunization related concerns, behavior problems, injury and accidents, and safety measures. The most frequent problems for counseling were physical signs and symptoms (27.3％), followed by feeding and nutrients, information on child rearing, and growth and development. Of physical problems, abnormal gastrointestinal signs and symptoms were the most frequent concern and skin problems were next at 25％ and 23.3％ respectively. Loose bowels, vomiting and constipation were the most frequent gastrointestinal problems. Atopic dermatitis had the highest frequency at 53.3％ with diaper rash being the second highest among the skin problems. About 80％ of the growth and developmental category were physical development concerns related to physiological, body growth, and motor and sensory development. This study constitutes the activity report for the first year of the Center. The findings correspond with literature reports on child health problems and parents educational needs. One recommendation from this study is that since the services of the Center are carried out only by telephone, the psychology of the counselees and the counselor relationship must be considered for better services.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.7
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• pp.1148-1156
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• 2013

Studies have shown that the preference and average consumption of kimchi among youths have been decreasing partly due to the westernization of the diet. In this study, we examined kimchi consumption status and the annual utilization of 29 kimchi menus registered in the National Education Information System (NEIS) among the students, and then developed seven kimchi menus based on the preference tests and plate waste analysis. Our findings showed that average kimchi consumption by second and fifth graders during lunch time was 19.3% and 17.3%, respectively, of the recommendation (40 g per meal) in the 2010 KDRI. Incidentally, more than 75% of elementary school dieticians answered that ten kimchi menus (31%) registered in the NEIS were never chosen by them in the previous year. The least adopted types of kimchi menu included cooked rice, porridge, stew, pancake, deep-fry and grill. The newly developed kimchi menus included kimchi sauce tofu deopbap, kimchi bacon rice ball, kimchi chicken potato stew, kimchi vegetable fried noodles, kimchi meatballs, kimchi cheese croquette and kimchi potato salad. All these kimchi food items contained 10~20 g of kimchi per serving, and the standardized recipes and nutrient analysis were provided. Kimchi cheese croquette was most liked by fourth graders followed by kimchi sauce tofu deopbap, kimchi meatball and kimchi chicken potato stew in that order. These four menus were again evaluated among second and fifth graders. The kimchi meatballs were most preferred among these groups of students with no leftover but kimchi sauce tofu deopbap was least favorable, producing 17.1% of plate waste. Finally, kimchi cheese croquette and kimchi potato salad were given the highest and lowest scores, respectively, by 87 school dieticians. The findings of this study suggest that efforts on the development of kimchi menu for school food services may help to promote a preference and consumption of kimchi among elementary school students.

• Journal of Agricultural Extension & Community Development
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• v.7 no.1
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• pp.121-136
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• 2000

This study reports on a comparison between the Korean diffusion of agricultural innovation or extension service and the cooperative extension service in the United States of America. It focuses on relevant differences between the two systems and provides recommendation for improvement of the Korean system to insure success in important areas related to the diffusion of agricultural innovations. After a comparative study on diffusion of innovations it is clear that: in order to have a productive agriculture that makes effective and efficient use of natural resources and helps achieve sustainability goals, a mechanism that delivers knowledge to agricultural communities must be established and maintained. This mechanism is clearly an agricultural extension service that is cooperatively funded by federal, state and local governments and that insures participation of constituents in the process of establishing priorities and evaluating achievements. The success of US agriculture, the most productive in the world, is to a large degree to the Cooperative Extension Service. Based on the results of this study and the differences of the United States and Korea, the following recommendations should be emphasized for more effective communication for agricultural innovation and rural development in Korea: 1) In order to insure that extension educators are high caliber professional individuals, it is important to establish a system that nationally recognizes these individuals as such, and that provides a professional development path. 2) The results of the decision of transfer of extension educators to local governments has not yielded positive outcomes, especially in terms of professional status. It is clearly demonstrable that valuable professionals are leaving the service, that local governments do not have the will and resources to implement a successful extension program. 3) Because of the critical importance of diffusing innovations to agricultural producers in order to insure and quality and steady food supply, it is of critical importance that these issues be addressed before the extension service is further deteriorated. Given the cement situation, it is clear that the extension service should become nationally supported again in cooperation with local and state governments and that extension professionals be given appropriate rank at the national level, commesurate with their peers in research and teaching. 4) The common current committee practice of lengthy reporting and short discussion needs to be changed to one that results in char, brief and substantive action oriented goals. Joint participation by researchers, extension educators and farmers should be encouraged in planning, implementation and evaluation of communication for agricultural innovations. Roles and functions of committees for institutional cooperation, and or agricultural extension committees should be enlarged. 5) Extension educators should be encouraged to adopt new communication technologies to improve their diffusion of innovations methods. Agricultural institutions and organizations should be encouraged to adopt farmer-first and or client-oriented approach in agricultural extension and diffusion of agricultural technologies. The number, complexity and rapid change of information in agricultural extension require the development of a computer based information and report system to support agricultural extension. 6) To facilitate and expand the further development of communication for agricultural innovation and rural development, agricultural communication programs in universities especially in colleges of agriculture and life sciences. 7) To strengthening the sense of national and social responsibility communication for agricultural innovation and rural development among students in agricultural colleges and universities through participation in learning activities by proactive recruitment. 8) To establish and reinforce a policy that insures participation in communication for agricultural innovation and regal development activities. 9) To improve further development of communication for agricultural innovation and rural development in Korea, more research activities should be encouraged.

• Radiation Oncology Journal
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• v.20 no.4
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• pp.381-390
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• 2002

Purpose : To develop a dose calibration program for the IAEA TRS-277 and AAPM TG-21, based on the air kerma calibration factor (or the cavity-gas calibration factor), as well as for the IAEA TRS-398 and the AAPM TG-51, based on the absorbed dose to water calibration factor, so as to avoid the unwanted error associated with these calculation procedures. Materials and Methods : Currently, the most widely used dosimetry Protocols of high energy photon beams are the air kerma calibration factor based on the IAEA TRS-277 and the AAPM TG-21. However, this has somewhat complex formalism and limitations for the improvement of the accuracy due to uncertainties of the physical quantities. Recently, the IAEA and the AAPM published the absorbed dose to water calibration factor based, on the IAEA TRS-398 and the AAPM TG-51. The formalism and physical parameters were strictly applied to these four dose calibration programs. The tables and graphs of physical data and the information for ion chambers were numericalized for their incorporation into a database. These programs were developed user to be friendly, with the Visual $C^{++}$ language for their ease of use in a Windows environment according to the recommendation of each protocols. Results : The dose calibration programs for the high energy photon beams, developed for the four protocols, allow the input of informations about a dosimetry system, the characteristics of the beam quality, the measurement conditions and dosimetry results, to enable the minimization of any inter-user variations and errors, during the calculation procedure. Also, it was possible to compare the absorbed dose to water data of the four different protocols at a single reference points. Conclusion : Since this program expressed information in numerical and data-based forms for the physical parameter tables, graphs and of the ion chambers, the error associated with the procedures and different user could be solved. It was possible to analyze and compare the major difference for each dosimetry protocol, since the program was designed to be user friendly and to accurately calculate the correction factors and absorbed dose. It is expected that accurate dose calculations in high energy photon beams can be made by the users for selecting and performing the appropriate dosimetry protocol.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Journal of radiological science and technology
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• v.32 no.3
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• pp.335-341
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• 2009

Purpose : The medical imaging issuance is changed from conventional film method to Digital Compact Disk solution because of development on IT technology. However other medical record department's are undergoing identification check through and through whereas medical imaging department cannot afford to do that. So, we examine present applicant's recognition of private intelligence safeguard, and medical imaging issuance condition by CD & DVD medium toward various medical facility and then perform comparative analysis associated with domestic and foreign law & recommendation, lastly suggest standard for medical imaging issuance and process relate with internal environment. Materials and methods : First, we surveyed issuance process & required documents when situation of medical image issuance in the metropolitan medical facility by wire telephone between 2008.6.1$\sim$2008.7.1. in accordance with the medical law Article 21$\sim$clause 2, suggested standard through applicant's required documents occasionally - (1) in the event of oneself $\rightarrow$ verifying identification, (2) in the event of family $\rightarrow$ verifying applicant identification & family relations document (health insurance card, attested copy, and so on), (3) third person or representative $\rightarrow$ verifying applicant identification & letter of attorney & certificate of one's seal impression. Second, also checked required documents of applicant in accordance with upper standard when situation of medical image issuance in Kyung-hee university medical center during 3 month 2008.5.1$\sim$2008.7.31. Third, developed a work process by triangular position of issuance procedure for situation when verifying required documents & management of unpreparedness. Result : Look all over the our manufactured output in the hospital - satisfy the all conditions $\rightarrow$ 4 place(12%), possibly request everyone $\rightarrow$ 4 place(12%), and apply in the clinic section $\rightarrow$ 9 place(27%) that does not medical imaging issuance office, so we don't know about required documents condition. and look into whether meet or not the applicant's required documents on upper 3month survey - satisfy the all conditions $\rightarrow$ 629 case(49%), prepare a one part $\rightarrow$ 416 case(33%), insufficiency of all document $\rightarrow$ 226case(18%). On the authority of upper research result, we are establishing the service model mapping for objective reception when image export situation through triangular position of issuance procedure and reduce of friction with patient and promote the patient convenience. Conclusion : The PACS is classified under medical machinery that mean indicates about higher importance of medical information therefore medical information administrator's who already received professional education & mind, are performer about issuance process only and also have to provide under ID checking process exhaustively.

• 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.