• Title/Summary/Keyword: BIG five

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Sales Volume Prediction Model for Temperature Change using Big Data Analysis (빅데이터 분석을 이용한 기온 변화에 대한 판매량 예측 모델)

  • Back, Seung-Hoon;Oh, Ji-Yeon;Lee, Ji-Su;Hong, Jun-Ki;Hong, Sung-Chan
    • The Journal of Bigdata
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    • v.4 no.1
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    • pp.29-38
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    • 2019
  • In this paper, we propose a sales forecasting model that forecasts the sales volume of short sleeves and outerwear according to the temperature change by utilizing accumulated big data from the online shopping mall 'A' over the past five years to increase sales volume and efficient inventory management. The proposed model predicts sales of short sleeves and outerwear according to temperature changes in 2018 by analyzing sales volume of short sleeves and outerwear from 2014 to 2017. Using the proposed sales forecasting model, we compared the sales forecasts of 2018 with the actual sales volume and found that the error rates are ±1.5% and ±8% for short sleeve and outerwear respectively.

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A Model of Predictive Movie 10 Million Spectators through Big Data Analysis (빅데이터 분석을 통한 천만 관객 영화 예측 모델)

  • Yu, Jong-Pil;Lee, Eung-hwan
    • The Journal of Bigdata
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    • v.3 no.1
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    • pp.63-71
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    • 2018
  • In the last five years (2013~2017), we analyzed what factors influenced Korean films that have surpassed 10 million viewers in the Korean movie industry, where the total number of moviegoers is over 200 million. In general, many people consider the number of screens and ratings as important factors that affect the audience's success. In this study, four additional factors, including the number of screens and ratings, were established to establish a hypothesis and correlate it with the presence of 10 million spectators through big data analysis. The results were significant, with 91 percent accuracy in predicting 10 million viewers and 99.4 percent accuracy in estimating cumulative attendance.

Analysis of Regional Transit Convenience in Seoul Public Transportation Networks Using Smart Card Big Data (스마트카드 빅데이터를 이용한 서울시 지역별 대중교통 이동 편의성 분석)

  • Moon, Hyunkoo;Oh, Kyuhyup;Kim, SangKuk;Jung, Jae-Yoon
    • Journal of Korean Institute of Industrial Engineers
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    • v.42 no.4
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    • pp.296-303
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    • 2016
  • In public transportation, smart cards have been introduced for the purpose of convenient payment systems. The smart card transaction data can be utilized not only for the exact and convenient payment but also for civil planning based on travel tracking of citizens. This paper focuses on the analysis of the transportation convenience using the smart card big data. To this end, a new index is developed to measure the transit convenience of each region by considering how passengers actually experience the transportation network in their travels. The movement data such as movement distance, time and amount between regions are utilized to access the public transportation convenience of each region. A smart card data of five working days in March is used to evaluate the transit convenience of each region in Seoul city. The contribution of this study is that a new transit convenience measure was developed based on the reality data. It is expected that this measure can be used as a means of quantitative analysis in civil planning such as a traffic policy or local policy.

A Study on Fruits Characteristics of the Chosen Dynasty through the Analysis of Chosenwangjoeshirok Big Data (빅데이터 분석을 통한 조선시대 과실류 특성 연구)

  • Kim, Mi-Hye
    • Journal of the Korean Society of Food Culture
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    • v.36 no.2
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    • pp.168-183
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    • 2021
  • Using the big data analysis of the Choseonwangjosilrok, this research aimed to figure out the fruits' types, prevalence, seasonal appearances as well as the royalty's perspective on fruits during Choseon period. Choseonwangjosilrok included nineteen kinds of fruits and five kinds of nuts, totaling 1,601 cases at 72.8% and 533 cases at 24.2% respectively. The text recorded fruits being used as: tributes for kings, gifts from kings to palace officials, tomb offerings, county specialties, trade goods or gifts to the foreign ambassadors, and medicine ingredients in oriental pharmacy. Seasonally the fruits appeared demonstrating an even distribution. Periodic characteristics were observed in decreasing quantity chronologically. From fifteenth century to nineteenth century, the fruits with timely features were seen: 804 times at 36.6%, 578 times at 26.3%, 490 times at 22.3%, 248 times at 11.3%, and 78 times at 3.5% respectively. In fifteenth century: citrons, quinces, pomegranates, cherries, permissions, watermelons, Korean melons, omija, walnuts, chestnuts, and pine nuts appeared most frequently. In sixteenth century: pears, grapes, apricots, peaches, and hazelnuts appeared most frequently. In seventeenth century: tangerines and dates appeared most frequently. In eighteenth century, trifoliate orange was the most frequently mentioned fruit.

Types and Characteristics Analysis of Human Dynamics in Seoul Using Location-Based Big Data (위치기반 빅데이터를 활용한 서울시 활동인구 유형 및 유형별 지역 특성 분석)

  • Jung, Jae-Hoon;Nam, Jin
    • Journal of Korea Planning Association
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    • v.54 no.3
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    • pp.75-90
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    • 2019
  • As the 24-hour society arrives, human activities in daytime and nighttime urban spaces are changing drastically, and the need for new urban management policies is steadily increasing. This study analyzes the types and characteristics of Seoul's human dynamics using location-based big data and the results are summarized as follows. First, the pattern of human dynamics in Seoul repeats itself every 7 days. Second, the types of human dynamics in Seoul can be classified into five types, and each of type has its own unique time-series and local characteristics. Third, the degree of match between human dynamics and zoning system in urban planning legislation was highest in 'Type 1' residence pattern and low in other types. The following implications can be drawn from these results. First, This paper examined the methodology of analyzing the regional characteristics of Seoul through the human dynamics and obtained meaningful results. Second, This paper can derive reliable and objective pattern analysis results using Big data that reflect the overall population characteristics. Third, the scale of night-time activity in the urban space of Seoul was understood, and its distribution, patterns and characteristics identified.

A Trend Analysis of Changes in Housework due to Technological Innovation and Family Change

  • LEE, Hyun-Ah;KWON, Soonbum
    • East Asian Journal of Business Economics (EAJBE)
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    • v.10 no.1
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    • pp.109-121
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    • 2022
  • Purpose - This study attempted to analyze news big data in order to examine the trend of change in housework due to technological innovation and family changes. Research design, data, and methodology - News big data was collected from Bigkinds for the purpose of trend analysis. A total of 8,270 articles containing 'housework' were extracted from news articles between January 1, 1990 and December 31, 2021. 11 general daily newspapers and 8 business newspapers were selected and were analyzed by dividing them into five-year units. Result - The change of trends in housework that appeared through news big data analysis can be summarized as below. First, the tendency to regard housework as work of women or housewives is gradually weakening. Instead, the centrality of connection with double income is increasing. Second, there is a tendency to strengthen the institutional approach to evaluation of the productivity of housework. Third, the possibility of market substitution for housework is expanding. Conclusion - In the era of the 4th industrial revolution, examining the impact of technological innovation and family change on housework not only enables the prospect of an industry, but also provides implications for policies related to housework. In addition, this study is differentiated in that it contributed to expand the field of housework research previously limited to analyzing survey data.

A Study on the Constrained Dispatch Scheduling Using Affine Scaling Interior Point Method (Affine Scaling Interior Point Method를 이용한 제약급전에 관한 연구)

  • Kim, Kyung-Min;Han, Seok-Man;Chung, Koo-Hyung;Kim, Bal-Ho
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.55 no.3
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    • pp.133-138
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    • 2006
  • This paper presents an Optimal Power Flow (OPF) algorithm using Interior Point Method (IPM) to swiftly and precisely perform the five minute dispatch. This newly suggested methodology is based on Affine Scaling Interior Point Method which is favorable for large-scale problems involving many constraints. It is also eligible for OPF problems in order to improve the calculation speed and the preciseness of its resultant solutions. Big-M Method is also used to improve the solution stability. Finally, this paper provides relevant case studies to confirm the efficiency of the proposed methodology.

Big Data Analytics of Construction Safety Incidents Using Text Mining (텍스트 마이닝을 활용한 건설안전사고 빅데이터 분석)

  • Jeong Uk Seo;Chie Hoon Song
    • Journal of the Korean Society of Industry Convergence
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    • v.27 no.3
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    • pp.581-590
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    • 2024
  • This study aims to extract key topics through text mining of incident records (incident history, post-incident measures, preventive measures) from construction safety accident case data available on the public data portal. It also seeks to provide fundamental insights contributing to the establishment of manuals for disaster prevention by identifying correlations between these topics. After pre-processing the input data, we used the LDA-based topic modeling technique to derive the main topics. Consequently, we obtained five topics related to incident history, and four topics each related to post-incident measures and preventive measures. Although no dominant patterns emerged from the topic pattern analysis, the study holds significance as it provides quantitative information on the follow-up actions related to the incident history, thereby suggesting practical implications for the establishment of a preventive decision-making system through the linkage between accident history and subsequent measures for reccurrence prevention.

A Study on the Application Methods of Big Data in the Technology Commercialization Process (기술사업화 프로세스 단계별 빅데이터 활용방안에 관한 연구)

  • Park, Chang-Gul;Roh, Hyun-Suk;Choi, Yun-Jeong;Kim, Hyun-Woo;Lee, Jae Kwang
    • The Journal of Society for e-Business Studies
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    • v.19 no.4
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    • pp.73-99
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    • 2014
  • Recently, big data have been studied ways to use in various fields. Big data refers to huge amounts of data that could not be addressed by conventional methods. Big data has attracted attention for improving accuracy of decision-making, forecasting in the near future, and creation of new business. In this study, it is an object to develop the utilization plan for big data in the field of technology commercialization. For this reason, we conducted study like case studies, literature review and focus group interview. We have derived the big data utilization plan based on this in the technology commercialization field. It, the data utilization plan, combines with the technology commercialization process of Jolly and it has five sub processes (Imagining, Incubating, Demonstrating, Promoting, Sustaining). In this paper, there is a significance that has emphasized the possibility for big data utilization in the technology commercialization. However, there is a limit to the general interpretation for our study. And we hope to contribute to the expansion of areas of technology commercialization information analysis through this research.

The Strategic Decision-making and Its Impact on Corporate Performance in Korean Trading Conglomerates (한국 무역기업집단의 전략적 의사결정과 기업성과)

  • Joo, In-Woo;Park, Chong-Don
    • International Commerce and Information Review
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    • v.13 no.3
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    • pp.543-564
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    • 2011
  • In the process of managing organization, the strategic decision-making and corporate performance are not independent, but they are interdependent each other. In most Korean firms, decision-making power and authority are concentrated on the higher echelons of managerial hierarchies. Examining big five trading conglomerates in Korea, this present paper investigates the relationship between strategic decision-making and a corporate performance. Although a number of review studies on Korean management have been developed over the years, there have been less works designed with decision making in mind. In order to achieve research objectives, this paper predicted some hypotheses, and the major findings include: 1) the influence of Korea's long-standing Confucian tradition and culture dominated across organizations, there have not been significant changes in decision-making process within big five trading firms; 2) top executives' excessive involvement in decision-making process does not hinder corporate performance. This result implies that the decision power is still tended to be centralized in the hands of the top management. 3) However, the power of Board of Directors in decision-making has become increasingly important; and 4) decision makers do not tend to misuse or abuse their political position and power for their own interests.

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