• Title/Summary/Keyword: Portal analysis

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SNS Operation Status Analysis and Improvement Plan for Facilitating of Use of Open Data Portal (공공데이터포털 이용 활성화를 위한 SNS 운용현황 및 개선방안)

  • Hwang, Sung-Wook;Jung, Yeyong;Kim, Soojung;Oh, Hyo-Jung
    • Journal of the Korean Society for information Management
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    • v.37 no.2
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    • pp.23-45
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    • 2020
  • The world is paying attention to the South Korean government's aggressive COVID-19 response, key of which is transparency and openness in sharing information. Opening up government information is essential to enhancing its social and economic value through increased awareness and accessibility. The purpose of this study is to investigate the current status of SNS operated by national open data portals in which government-collected and -disclosed data is available and to suggest improvements for the use of open data portals. To do this, the study compared 3 national open data portals, each from India, U.S.A, and Korea, by performing quantitative analysis, user feedback analysis, time-series analysis, and information type analysis. Based on the identified information types and user needs, the study suggests concrete ways to facilitate the use of open data portals.

An Analysis of the Time-Lag Effects on the Investment of G4C E-Government System by analysing DB Data (운영 DB데이터 분석을 통한 G4C 전자정부 정보화 사업 투자 시차효과 분석)

  • Cho, Nam-Jae;Lim, Gyoo-Gun;Lee, Dae-Chul
    • Journal of Information Technology Applications and Management
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    • v.16 no.4
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    • pp.205-222
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    • 2009
  • Considering time-lag in the performance evaluation of information system (IS) investment is important because its effect reveals after certain period of time passed. Particularly it is more in the systems of e-government informatization projects which the amount of investment and the scale of business are huge. Many methods to solve this issue have been proposed such as system dynamics methods, simulations, structural equations etc. However, it is still difficult and unsolved problem because collecting practical data for time-lag analysis is very hard. In this paper, we analyze IS time-lag effect through factor analysis using the accumulated practical operational DB data. For the performance evaluation of the G4C system, the representative e-government web portal, we selected eleven factors reflecting time passing in G4C DB data. With these factors this paper conduct time-lag analysis in four view points. First, we conducted 'Stabilizing of G4C system' and got a result that IS is needed about three years for the stabilization. Second, we conducted 'Utilization of G4C system' and got a result that the utilization reaches appropriate level after in three years later after the introduction of G4C system. Third, we conducted 'Cost reduction effect' and got a result that cost reduction is stable in the third year after the introduction of G4C system. Lastly, we conducted 'System maturity effect' and got a result that the system reaches to the quality level that users expect after third to fourth years. According to the results of this research, we found that performance of IS improv continuously not immediately, and it needs three or four years of time-lag.

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Changes in consumer perception of fashion products in a pandemic - Effects of COVID-19 spead - (팬데믹 상황에서의 패션제품에 대한 소비자의 인식 변화 분석 - 코로나19 확산의 영향 -)

  • Choi, Yeong-Hyeon;Lee, Kyu-Hye
    • The Research Journal of the Costume Culture
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    • v.28 no.3
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    • pp.285-298
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    • 2020
  • This study aimed at examining fashion consumers' awareness during the COVID-19 pandemic. Big data analysis methods, such as text mining, social network analysis, and regression analysis, were applied to user posts about fashion on Korean portal websites and social media during COVID-19. R 3.4.4, UCINET 6, and SPSS 25.0 software were used to analyze the data. The results were as follows. In researching the popular fashion-related topics during COVID-19, the prevention of infection and prophylaxis were significant concerns in the early stage (Jan 1 to Jan 31, 2020), and changed to online channels and online fashion platforms. Then, various topics and fashion keywords appeared with COVID-19-related keywords afterwards. Fashion-related subjects concerned prophylaxis, home life, digital and beauty products, online channels, and fashion consumption. In comparing fashion consumers' awareness during COVID-19 with SARS and MERS, "face masks" was the common keyword for all three illnesses; yet, the prevention of infection was a major consumer concern in fashion-related subjects during COVD-19 only. As COVD-19 cases increased, the search volume for face masks, shoes, and home clothes also increased. Consumer awareness about face masks shifted from blocking yellow dust and micro-dust to the sociocultural significance and short supply. Keywords related to performance turned out to be the major awareness as to shoes, and home clothes were repurposed with an expanded range of use.

Metadata Analysis of Open Government Data by Formal Concept Analysis (형식 개념 분석을 통한 공공데이터의 메타데이터 분석)

  • Kim, Haklae
    • The Journal of the Korea Contents Association
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    • v.18 no.1
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    • pp.305-313
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    • 2018
  • Public open data is a database or electronic file produced by a public agency or government. The government is opening public data through the open data portals and individual agency websites. However, it is a reality that there is a limit to search and utilize desired public data from the perspective of data users. In particular, it takes a great deal of effort and time to understand the characteristics of data sets and to combine different data sets. This study suggests the possibility of interlinking between data sets by analyzing the common relationship of item names held by public data. The data sets are collected from the open data portal, and item names included in the data sets are extracted. The extracted item names consist of formal context and formal concept through formal concept analysis. The format concept has a list of data sets and a set of item name as extent and intent, respectively, and analyzes the common items of intent end to determine the possibility of data connection. The results derived from the formal concept analysis can be effectively applied to the semantic connection of the public data, and can be applied to data standard and quality improvement for public data release.

Consumers' perceptions of professional laundry shops using semantic network analysis (의미 네트워크 분석을 활용한 세탁전문점에 대한 소비자 인식 연구)

  • Kim, Ji-Yeon;Lee, Kyu-Hye
    • The Research Journal of the Costume Culture
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    • v.27 no.6
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    • pp.645-653
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    • 2019
  • Laundry services are becoming more specialized and diversified. Therefore, this study investigated consumers' perceptions of professional laundry shops by analyzing social media data. For this purpose, text data from blogs, cafés, and Q&A sections ('Ji-Sik-In') on the portal site, naver.com, was collected. Sixty-four keywords were extracted from 2,213 social texts and transformed into a one-mode matrix using KrKwic, a program for the analysis of Korean text. Semantic network analysis was conducted to understand the network structure and the results were visualized using NodeXL. Keywords included fashion items and materials that require specialized professional laundry services, words related to the establishment of laundry shops, and laundry shop brands. Essential keywords of professional laundry shops included 'luxury,' 'footwear,' 'removal,' 'bag,' 'leather,' 'sneakers,' 'padding,' 'premium,' 'dyeing,' and 'franchise.' These results could be used to deduce that consumers perceive a professional laundry shop as a franchise shop offering specialized professional laundry services. A cluster analysis was conducted to identify the types of consumer perceptions of professional laundry shops. The network was divided into three groups: 'specialized professional laundry service,' 'laundry and repair of winter coats and jackets,' and 'the establishment of a professional laundry shop.' According to the results, consumers perceive professional laundry shops as franchises that offer specialized professional laundry services rather than general laundry services. Therefore, professional laundry shops need a strategy to develop special laundry services that differentiate them from other companies and communicate with consumers about these services.

Image Analysis and Management Strategy for The National Science Museum Utilizing SNS Big Data Analysis (SNS 빅데이터 분석을 활용한 국립과학관에 대한 이미지 분석과 경영전략 제안)

  • Shin, Seongyeon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.1
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    • pp.81-89
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    • 2020
  • The purpose of this study is to investigate science consumers' perceptions of the National Science Museum and suggest effective management strategies for the museum. Research questions were established and the analyses were conducted to achieve the research goals. The collection and analysis of the data were conducted through a new approach to image analysis that combines qualitative and quantitative methods. First, the image of the concept of science was derived from science consumers (adults, undergraduate and graduate students) through a qualitative research method (group-interviewing), and then text analysis was conducted. Second, quantitative research was conducted through LDA (Latent Dirichlet Allocation)-based topical modeling of 63,987 words extracted from 12,920 titles of blog postings from one of the most heavily-trafficked portal sites in Korea. The results of this study indicate that the perception of science differs according to the characteristics of the respondents. Further, topic-modeling extracted 20 topics from the blog posting titles and the topics were condensed into seven factors. Detailed discussions and managerial implications are provided in the conclusion section.

A Study on the Development of Product Planning Prediction Model Using Logistic Regression Algorithm (로지스틱 회귀 알고리즘을 활용한 상품 기획 예측 모형 개발에 관한 연구)

  • Ahn, Yeong-Hwil;Park, Koo-Rack;Kim, Dong-Hyun;Kim, Do-Yeon
    • Journal of the Korea Convergence Society
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    • v.12 no.9
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    • pp.39-47
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    • 2021
  • This study was conducted to propose a product planning prediction model using logistic regression algorithm to predict seasonal factors and rapidly changing product trends. First, we collected unstructured data of consumers in portal sites and online markets using web crawling, and analyzed meaningful information about products through preprocessing for transformation of standardized data. The datasets of 11,200 were analyzed by Logistic Regression to analyze consumer satisfaction, frequency analysis, and advantages and disadvantages of products. The result of analysis showed that the satisfaction of consumers was 92% and the defective issues of products were confirmed through frequency analysis. The results of analysis on the use satisfaction, system efficiency, and system effectiveness items of the developed product planning prediction program showed that the satisfaction was high. Defective issues are very meaningful data in that they provide information necessary for quickly recognizing the current problem of products and establishing improvement strategies.

A Systematic Review and Meta-Analysis of Randomized Controlled Trials on Chuna Manual Therapy for Cervicogenic Headache

  • Lee, Dong-Wha;Kim, Ju-Young;Hong, Min-Ho;Koo, Byung-Soo;Kim, Geun-Woo
    • Journal of Oriental Neuropsychiatry
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    • v.30 no.2
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    • pp.89-105
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    • 2019
  • Objectives: We conducted this study to evaluate the efficacy of Chuna Manual Therapy (CMT) for treatment of cervicogenic headache (CeH) through systematic review and Meta-analysis of randomized controlled trials (RCTs) as a preceding research to further research the effective of Chuna Manual Therapy for patients who suffered from CeH. Methods: We conducted a systematic review and meta-analysis by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched the studies from MEDLINE, Elsevier-EMBASE, The Cochrane Library, CAJD, KISS, KMBase, Korean Traditional Knowledge Portal, NDSL, and OASIS. The studies selected only in randomized controlled trials. We selected the chosen studies by the selection and the exclusion criteria, and evaluated the quality of the selected studies using the Jadad score and the Cochran ROB tool. We used the Visual Analogue Scale score (VAS) and Clinical total Effective Rate (CER) for the results and analyzed the results of the included studies using RevMan 5.3 software provided by the Cochran library. Results: We included 20 RCTs, including 1,673 subjects, in the systematic review and meta-analysis. After the intervention, the CMT group showed better results than the pharmacotherapy group, the physiotherapy group, and the combined treatment group. The CMT group showed a good effect on the CER and the VAS but showed a significant heterogeneity compared to the pharmacotherapy group. Conclusions: The CMT as monotherapy might have benefits on Cervicogenic Headache patient. Further well-designed studies need to be conducted.

Comparative Analysis of Ship Departure Status by Major Ports in Korea (한국 내 주요 항만별 선박출항현황 비교 분석)

  • Choi, Jeong-Il
    • The Journal of the Korea Contents Association
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    • v.21 no.3
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    • pp.454-462
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    • 2021
  • The purpose of this paper is to compare and analyze the status of ship departures by major ports in Korea. To this end, we collected necessary data from the National Statistical Office (National Statistical Portal), "Transportation·Logistics ⇨ Ship Departure Status by Port". The analysis period is 141 months from January 2009 to September 2020. The increase rate was higher in the order of Yeosu, Pyeongtaek Dangjin, Gwangyang, Busan, Incheon and Ulsan. In the analysis of the rate of change, Yeosu showed an uptrend while other ports showed a modest downtrend. In the scatter analysis, the total ship departure shows a high degree of synchronization with other ports except Yeosu. As a result of the empirical analysis, the recent trend of ship departures is slowly falling below 0%, and the current movement is expected to continue for the time being. As the southern logistics of China and ASEAN and northern logistics of Eurasia become active, the role of major ports is expected to expand further. It is necessary to develop a differentiated logistics service for each port and find an efficient way to increase the volume of goods by deriving factors for improving logistics.

Regional Image Change Analysis using Text Mining and Network Analysis (텍스트 마이닝과 네트워크 분석을 이용한 지역 이미지 변화 분석)

  • Jeong, Eun-Hee
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.15 no.2
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    • pp.79-88
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    • 2022
  • Social media big data includes a lot of information that can identify not only consumer consumption patterns but also local images. This paper was collected annually data including 'Samcheok' from 2015 to 2019 from Blog and Cafe of Naver and Daum in domestic portal site, and analyzed the regional image change after refining keyword which forms the regional image by performing text mining and network analysis. According to the research results, the regional image of 2015 was expressed with image cognitive elements of the nearby place name or place etc. such as 'Jangho Port', 'Donghae', and 'Beach'. However the regional image both 2016 and 2019 were changed with image cognitive elements of 'SamcheokSolbich' which is a special place within region. Therefore as the keywords related to the local image include 'Jangho Port' and Resort, which are the representative attractions of Samcheok, it can be seen that the infrastructure factor plays a big role in forming the local image. The significance test for the network data used the bootstrap technique, and the p-values in 2015, 2016, and 2019 were 0.0002, 0.0006, and 0.0002, respectively, which were found to be statistically significant at the significance level of 5%.