• Title/Summary/Keyword: Industry classification

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A Box Office Type Classification and Prediction Model Based on Automated Machine Learning for Maximizing the Commercial Success of the Korean Film Industry (한국 영화의 산업의 흥행 극대화를 위한 AutoML 기반의 박스오피스 유형 분류 및 예측 모델)

  • Subeen Leem;Jihoon Moon;Seungmin Rho
    • Journal of Platform Technology
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    • v.11 no.3
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    • pp.45-55
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    • 2023
  • This paper presents a model that supports decision-makers in the Korean film industry to maximize the success of online movies. To achieve this, we collected historical box office movies and clustered them into types to propose a model predicting each type's online box office performance. We considered various features to identify factors contributing to movie success and reduced feature dimensionality for computational efficiency. We systematically classified the movies into types and predicted each type's online box office performance while analyzing the contributing factors. We used automated machine learning (AutoML) techniques to automatically propose and select machine learning algorithms optimized for the problem, allowing for easy experimentation and selection of multiple algorithms. This approach is expected to provide a foundation for informed decision-making and contribute to better performance in the film industry.

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A Study on the policy for export competitiveness enforcement of Korean Service Industry (한국 서비스산업의 수출경쟁력 강화정책에 관한 연구)

  • Lee, Ho-Gun
    • International Commerce and Information Review
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    • v.15 no.4
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    • pp.97-122
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    • 2013
  • Korea's trade balance in service showed surplus in 2012 on the basis of BPM5. This is recorded by 14 years since 1999. This owes to decrease of deficit in tourism balance, increase of surplus in construction and transportation, and shift from deficit to surplus, even in small portion, in personal cultural recreational services balance. While externally the global economic growth becomes inactive and the Korean Won has appreciated, internally Korean service industry is very weak and is not equipped with international competitiveness. This study intends to look into service surplus items and services deficit items and to present measures that will be able to strengthen competitiveness in service industry. As a short case study, German and Japan was benchmarked, as they are the countries which are developed on the basis of manufacturing like Korea. And in this study, by analyzing surplus items and deficit items in trade balance sheet, it is attempted to suggest policies which would be available for strengthening service industry. As the service industry is a highly value-added one, it is necessary to designate promising categories and intensively foster as strategic industry. Service industry has their own characteristics distinguished with manufacturing goods. It has very different logistics and payment system with manufacturing industry. It means there must be independent support systems which reflect the nature of industrial classification in service industry. It is necessary to provide export support system, to organize export market development group, to support marketing, to set common logistics center, to support diplomatic means, to provide legal service and so on.

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An Analysis on the Economic Impact of China's Education Industry (중국 교육산업의 경제적 파급효과에 대한 분석)

  • Sang, Li;Zhang, Yizhou;Zhang, Mengze
    • The Journal of the Korea Contents Association
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    • v.21 no.9
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    • pp.299-311
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    • 2021
  • The purpose of this study is to analyze the ripple effect of the Chinese education industry on the national economy by using the industry-related table of 2017 by the China Statistical Office to use it as policy data for revitalization of the Chinese education industry in the future. To achieve this purpose, 149 industries in the basic classification of the industry-related table were classified into 32 industries. Based on these classifications, by analyzing the production induction coefficient, sensitivity coefficient, influence coefficient, yield inducement coefficient, production tax induction coefficient, and labor induction coefficient, etc. The purpose of this study is to understand the relationship between different industries and to find out the economic impact of the Chinese education industry. The analysis results show that in 2017, the total production induction coefficient of China's education industry was 1.7188, the row total was 1.0626, the sensitivity coefficient was 0.01211, the influence coefficient was 0.01958, the income induction coefficient was 0.6667, the production tax induction coefficient was 0.035, and the final demand was 1 billion yuan. When this occurs, the labor induction coefficient shows a total of 31,254 persons (indirect 15,541 persons, direct 15,713 persons). Based on the analysis results, this study suggested the implications that government support, technology introduction and application of new operating models, policy regulations, and efficient supervision of the system and president are required for further development of the Chinese education industry.

Classification of Parent Company's Downward Business Clients Using Random Forest: Focused on Value Chain at the Industry of Automobile Parts (랜덤포레스트를 이용한 모기업의 하향 거래처 기업의 분류: 자동차 부품산업의 가치사슬을 중심으로)

  • Kim, Teajin;Hong, Jeongshik;Jeon, Yunsu;Park, Jongryul;An, Teayuk
    • The Journal of Society for e-Business Studies
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    • v.23 no.1
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    • pp.1-22
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    • 2018
  • The value chain has been utilized as a strategic tool to improve competitive advantage, mainly at the enterprise level and at the industrial level. However, in order to conduct value chain analysis at the enterprise level, the client companies of the parent company should be classified according to whether they belong to it's value chain. The establishment of a value chain for a single company can be performed smoothly by experts, but it takes a lot of cost and time to build one which consists of multiple companies. Thus, this study proposes a model that automatically classifies the companies that form a value chain based on actual transaction data. A total of 19 transaction attribute variables were extracted from the transaction data and processed into the form of input data for machine learning method. The proposed model was constructed using the Random Forest algorithm. The experiment was conducted on a automobile parts company. The experimental results demonstrate that the proposed model can classify the client companies of the parent company automatically with 92% of accuracy, 76% of F1-score and 94% of AUC. Also, the empirical study confirm that a few transaction attributes such as transaction concentration, transaction amount and total sales per customer are the main characteristics representing the companies that form a value chain.

The Change of Industrial Distribution Pattern by Worker Status Classification : Busan, 1994~2004 (종사상 지위분류에 따른 산업분포변화: 부산, 1994~2004)

  • Kang, In-Joo;Nam, Kwang-Woo
    • Journal of the Korean Association of Geographic Information Studies
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    • v.10 no.4
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    • pp.111-121
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    • 2007
  • Diagnosis and Prediction of urban industrial structure is a key subject for establishment of sustainable urban development plan. By this time, studies of industry-related urban spatial structure have been concentrated on measurement of space distribution by industry type mainly using data about urban industries or total worker numbers. Now, status of workers become an important issue so this study analyzed qualitative change of urban industrial structure in the view of space using work status classification system. For that, data for work status in 1994 and 2004 were collected in towns and villages, and space analysis units were coincided based on change data between 1994 and 2004. Then, it analyzed spatial distribution pattern of employment through qualitative standard called work status using GIS. The analysis results by work status type of Busan industrial structure in GIS circumstance were as below. First, traditional labor intensive industries met a limit and service and wholesale/retail sale industries went to be poor livelihood. Therefore, Busan's employment rate should be decreased and worker numbers were statistically increased, however, irregular and non-wage workers were suddenly increased. So, it was determined that the quality of employment in Busan area came down. Second, a traditional downtown area has dwindled; on the other hand, employment has been increased in new town or new industrial complex and in the area developed services rather than the manufacturing industry. It is expected that the result of this study may be meaningful as data to prepare for longterm industrial development plan through qualitative evaluation called work status as well as to make behavior pattern of industrial structure which is basis of urban development.

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The Information Modeling Method based on Extended IFC for Alignment-based Objects of Railway Track (선형중심 객체 관리를 위한 확장된 IFC 기반 철도 궤도부 정보모델링 방안)

  • Kwon, Tae Ho;Park, Sang I.;Seo, Kyung-Wan;Lee, Sang-Ho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.31 no.6
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    • pp.339-346
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    • 2018
  • An Industry Foundation Classes(IFC), which is a data schema developed focusing on architecture, is being expanded to civil engineering structures. However, it is difficult to create an information model based on extended IFC since the BIM software cannot provide support functions. To manage a railway track based on the extended IFC, this paper proposed a method to create an alignment-centered separated railway track model and convert it to an extended IFC-based information model. First, railway track elements have been classified into continuous and discontinuous structures. The continuous structures were created by an alignment-based software, and discontinuous structures were created as independent objects through linkage of the discretized alignment. Second, a classification system and extended IFC schema for railway track have been proposed. Finally, the semantic information was identified by using the property of classification code and user interface. The availability of the methods was verified by developing an extended IFC-based information model of the Osong railway site.

A Comparative Study on Prediction Performance of the Bankruptcy Prediction Models for General Contractors in Korea Construction Industry

  • Seung-Kyu Yoo;Jae-Kyu Choi;Ju-Hyung Kim;Jae-Jun Kim
    • International conference on construction engineering and project management
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    • 2011.02a
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    • pp.432-438
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    • 2011
  • The purpose of the present thesis is to develop bankruptcy prediction models capable of being applied to the Korean construction industry and to deduce an optimal model through comparative evaluation of final developed models. A study population was selected as general contractors in the Korean construction industry. In order to ease the sample securing and reliability of data, it was limited to general contractors receiving external audit from the government. The study samples are divided into a bankrupt company group and a non-bankrupt company group. The bankruptcy, insolvency, declaration of insolvency, workout and corporate reorganization were used as selection criteria of a bankrupt company. A company that is not included in the selection criteria of the bankrupt company group was selected as a non-bankrupt company. Accordingly, the study sample is composed of a total of 112 samples and is composed of 48 bankrupt companies and 64 non-bankrupt companies. A financial ratio was used as early predictors for development of an estimation model. A total of 90 financial ratios were used and were divided into growth, profitability, productivity and added value. The MDA (Multivariate Discriminant Analysis) model and BLRA (Binary Logistic Regression Analysis) model were used for development of bankruptcy prediction models. The MDA model is an analysis method often used in the past bankruptcy prediction literature, and the BLRA is an analysis method capable of avoiding equal variance assumption. The stepwise (MDA) and forward stepwise method (BLRA) were used for selection of predictor variables in case of model construction. Twenty two variables were finally used in MDA and BLRA models according to timing of bankruptcy. The ROC-Curve Analysis and Classification Analysis were used for analysis of prediction performance of estimation models. The correct classification rate of an individual bankruptcy prediction model is as follows: 1) one year ago before the event of bankruptcy (MDA: 83.04%, BLRA: 93.75%); 2) two years ago before the event of bankruptcy (MDA: 77.68%, BLRA: 78.57%); 3) 3 years ago before the event of bankruptcy (MDA: 84.82%, BLRA: 91.96%). The AUC (Area Under Curve) of an individual bankruptcy prediction model is as follows. : 1) one year ago before the event of bankruptcy (MDA: 0.933, BLRA: 0.978); 2) two years ago before the event of bankruptcy (MDA: 0.852, BLRA: 0.875); 3) 3 years ago before the event of bankruptcy (MDA: 0.938, BLRA: 0.975). As a result of the present research, accuracy of the BLRA model is higher than the MDA model and its prediction performance is improved.

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Environmental Impacts Assessment of the Wheat Flour Production Process Using the Life Cycle Assessment Method (LCA 기법을 이용한 소맥분 생산 공정의 환경 영향 평가)

  • Chu, Duk-Sung;Kwon, Hyuk-Ku;Kim, Jong-Geu;Lee, Jang-Hoon
    • Journal of Environmental Health Sciences
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    • v.34 no.1
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    • pp.62-69
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    • 2008
  • The life cycle assessment method for environmental impact assessment was used, in this study, to assess the production process of wheat flour which is the most important material in the food industry. Environmental impact assessments were compared between that of the Ministry of Environment, Republic of Korea (method I) with that of the Ministry of Commerce, Industry and Energy (method II). Life cycle inventories (LCI) was performed using internal and external databases and the production statistics database of company S. The procedure of life cycle impact assessment (LCIA) was followed in terms of classification, characterization, normalization and weighting to identify the key issues. The impact categories of method I were divided into 8 categories with consideration of : abiotic resources depletion, global warming, ozone depletion, photochemical oxidant creation, acidification and eutrophication. The impact categories of method II were divided into 10 categories with consideration of: abiotic resources depletion, global warming, ozone depletion, photochemical oxidant creation, acidification, eutrophication, human toxicity, freshwater aquatic ecotoxicity, marine aquatic ecotoxicity and terrestrial ecotoxicity.

The Classification and Management Plan of City for Sustainable Development (도시의 지속가능한 발전을 위한 유형분류 및 관리방안)

  • Lee, Woo-Sung;Jung, Sung-Gwan;Park, Kyung-Hun;You, Ju-Han;Kim, Kyung-Tae
    • Journal of Environmental Impact Assessment
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    • v.17 no.6
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    • pp.335-348
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    • 2008
  • The purpose of this study is to classify the cities on sustainability assessment score studied in advance using cluster analysis, to present efficient management and policy direction based on analysis of sustainability index in 45 cities of all over Gyeongsangnam and Gyeongsangbuk-do. According to the results of cluster analysis, 45 cities were classed into 4 clusters by "livable-welfare city", "environmental -ecological city", "scientific-technological city", and "industrial-economic city". The livable-welfare cities must keep superior environmental sustainability, promote small and medium sized business on regional characteristic. The environmental-ecological cities have to change agriculture into future environmental industry such as ecotourism, bio-industry and landscape agriculture. The scientific-technological cities are going to need support of government scale such as income enlargement of citizen and stable job security. Finally, the industrial-economic cities must increase environmental management plants and improve quality of life through securing green spaces, maintaining public peace and applying UIS because of low quality of environment and life.

A Study on Developing Database System for Management of WPS/PQR in Shipyard (조선소 WPS/PQR 관리 DB시스템 개발에 관한 연구)

  • Park, Ju-Yong;Kong, Ji-Hye;Park, Se-Jin;Nam, Sung-Gil
    • Journal of Welding and Joining
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    • v.34 no.1
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    • pp.47-53
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    • 2016
  • WPS/PQR is the essential documents for shipbuilding welding. WPS is the document containing the information related to welding procedure and PQR is the record of approval for welding procedure. Both documents should be approved by the ship owners and the classification societies. It is very important to manage these documents because the welding procedure using these documents could not be carried out before they are approved. Database is an useful tool to manage these documents. It can manage a number of documents and show the processing status of WPS/PQR documents. In this study, all documents related to WPS/PQR documents were investigated and analyzed in the viewpoint of DB. An appropriate DB system was designed for WPS/PQR and the related documents on the basis of CBD methodology. The DB system could make WPS/PQR documents easily and shortly. The grasp of the processing status of WPS/ PQR could help the good management of fabrication schedule in shipbuilding.