• Asia-Pacific Journal of Business
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• v.14 no.3
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• pp.241-250
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• 2023

Purpose - The purpose of this study was to investigate the perception of 'unmanned cafes' on the network through big data analysis, and to identify the latest trends in rapidly changing consumer perception. Based on this, I would like to suggest that it can be used as basic data for the revitalization of unmanned cafes and differentiated marketing strategies. Design/methodology/approach - This study collected documents containing unmanned cafe keywords for about three years, and the data collected using text mining techniques were analyzed using methods such as keyword frequency analysis, centrality analysis, and keyword network analysis. Findings - First, the top 10 words with a high frequency of appearance were identified in the order of unmanned cafes, unmanned cafes, start-up, operation, coffee, time, coffee machine, franchise, and robot cafes. Second, visualization of the semantic network confirmed that the key keyword "unmanned cafe" was at the center of the keyword cluster. Research implications or Originality - Using big data to collect and analyze keywords with high web visibility, we tried to identify new issues or trends in unmanned cafe recognition, which consists of keywords related to start-ups, mainly deals with topics related to start-ups when unmanned cafes are mentioned on the network.

• Journal of the Korean Professional Engineers Association
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• v.14 no.2
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• pp.52-61
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• 1981

In Korea Small-medium Companies Constitutes 96.5% of all of the mining and manufacturing industries, about 35.7% of the total production of value added business, an average of 35% of the actual export of industrial goods and 47.6% of employment since present at the end of 1979. Now then Small-medium Industry Companies organization style constitutes 78.6% of a form of private company and 81.2% of the total on an small scale under 50 persons inregular employee. Specially, the trouble of business management of the mining and manufacturing Companies in Korea are constituted average 28.3% of production management ill the worst trouble of business management from 1973 to 1979 and small-medium industry Companies are the same of about more than 30% of production management in the trouble of business management. In this cases, the status of production management is effected by small-medium industry companies are the style of non-system and non-organization, but then 13parts in production management operations have the many trouble problems. In this circumstances a change for the better of production management operations in small medium industry companies are suggested the application effects and achievement points of production management, it is suggested a kind of variety and a small quantity, production management system of small-medium industry Company. And then Industrial Engineering technics is applied systematic route and the company grow more than better its physical condition for the improve productivity applied system approach for production management. There for the chapter 4-5 of this paper treats of a rational production management system approach, it make a emphatic major point of high level of economic growth of small medium Industry enterprise.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1759-1767
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• 2017

Although Open API has been invigorated by advancements in the software industry, diverse types of malicious code have also increased. Thus, many studies have been carried out to discriminate the behaviors of malicious code based on API data, and to determine whether malicious code is included in a specific executable file. Existing methods detect malicious code by analyzing signature data, which requires a long time to detect mutated malicious code and has a high false detection rate. Accordingly, in this paper, we propose a method that analyzes and detects malicious code using association rule mining and an Naive Bayes classification. The proposed method reduces the false detection rate by mining the rules of malicious and normal code APIs in the PE file and grouping patterns using the DHP(Direct Hashing and Pruning) algorithm, and classifies malicious and normal files using the Naive Bayes.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.6 s.150
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• pp.700-706
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• 2006

As development of information technology, companies stress the need of knowledge management. Companies construct ERP system including knowledge management. But, it is not easy to formalize knowledge in organization. They experience that constructing information system help knowledge management. Now, we focus on engineering knowledge. Because engineering data contains experts' experience and know-how in its own, engineering knowledge is a treasure house of knowledge. Korean shipyards are leader of world shipbuilding industry. They have accumulated a store of knowledge and data. But, they don't have data mining tool to utilize accumulated data. This paper treats development of data mining tools for the utilization of shipbuilding knowledge based on genetic programming(GP).

• Journal of Service Research and Studies
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• v.1 no.1
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• pp.61-69
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• 2011

Data mining that can not be extracted with a simple query in the form of "useful" means to find information in large databases from the existing and unknown knowledge. It is based on this insight about the data can be defined as a gain. In this paper, we use the Internet to find useful patterns on the Web or saved data to the target Web site, which is to analyze the characteristics of users. A general statistical information on Internet users to the data by applying a relevance analysis, Internet use affect the amount of time to analyze the characteristics of Internet users. Only through experiments extracting data from the association rules, producing optimal results apply for the data pre-processing and algorithm for mining the Web to Internet users. characteristics were analyzed.

• Journal of Korea Game Society
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• v.15 no.4
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• pp.59-68
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• 2015

The progress in Information & Communication Technology enables data scientists to analyze big data for identifying peoples' daily lives and tacit preferences. A variety of industries already aware the potential usefulness of analyzing big data. However limited use of big data has been performed in game industry. In this research, we adopt data mining technique to analyze data gathered from a strategic simulation game. Decision Tree, Random Forest, Multi-class SVM, and Linear Regression techniques are used to find the most important variables to users' game levels. We provide practical guides for game design and usability based on the analyzed results.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.621-652
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• 2012

Software Estimations provide an inclusive set of directives for software project developers, project managers, and the management in order to produce more realistic estimates based on deficient, uncertain, and noisy data. A range of estimation models are being explored in the industry, as well as in academia, for research purposes but choosing the best model is quite intricate. Estimation by Analogy (EbA) is a form of case based reasoning, which uses fuzzy logic, grey system theory or machine-learning techniques, etc. for optimization. This research compares the estimation accuracy of some conventional data mining models with a hybrid model. Different data mining models are under consideration, including linear regression models like the ordinary least square and ridge regression, and nonlinear models like neural networks, support vector machines, and multivariate adaptive regression splines, etc. A precise and comprehensible predictive model based on the integration of GRA and regression has been introduced and compared. Empirical results have shown that regression when used with GRA gives outstanding results; indicating that the methodology has great potential and can be used as a candidate approach for software effort estimation.

• Journal of Distribution Science
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• v.22 no.3
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• pp.71-81
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• 2024

Purpose: This study examines the impact of inclusive policies and green transformation on regional development of mining areas. Research design, data and methodology: We designed and utilized a structured questionnaire to collect data from a population of 300 individuals. The questionnaire was disseminated through Google Forms and consisted of five questions for each research variable. A total of 210 respondents completed the questionnaire, yielding a response rate of 70%. The sample was diverse in terms of gender and educational level Of the 210 respondents, 113 were female (53.8%) and 97 were male (46.2%). In terms of educational background, the sample was composed as follows: 13 individuals with a Doctorate degree (6.2%), 56 with a Master's degree (26.7%), 97 with a Bachelor's degree (46.2%), 22 with a Diploma (10.5%), and 22 with a High School education (10.5%). Results: The research outcomes highlight the significant influence of inclusive policies on driving the Distribution of green economic transformation. Emphasizing the pivotal role of inclusive distribution strategies, especially within the context of mining areas, the study sheds light on their crucial contribution to fostering regional development. Conclusion: These findings hold valuable implications for policymakers, industry stakeholders, and academics promoting environmentally conscious economic transformations.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.1
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• pp.9-22
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• 2009

This paper is an explanation of a design and an implementation of Web 2.0 online travel agency system for frequent decision-making. On the Web 2.0 travel agency system, optimized information is obtained by applying data mining technology such as association rules, decision trees, and neural networks, and this system is a unified system that consists of the block systems of hotels, ground traffic, and flights in tour packages of a travel agency system. Furthermore, it is implemented to manage the system that is not for the administrator of a travel agency system, but for users or communities that use the system need their own information. The expected effect of this system is to maximize the investment company's efficiency through a new-concept interest model created by B2C customers, and also B2B small and medium-sized travel agencies adopting the system. As a result, it is a system that stimulates dormant customer activity and prevents good customers from leaving by maximizing the merit and capacity of the existed web site for marketing. Moreover, this system is also a model for people who plan customized travel agency business, and will show a way for the domestic and international travel agency industry's globalization.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.813-818
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• 2007

Construction productivity is a key factor for efficiency evaluation of construction work process, project performance measurement, and basic data of work plan in construction industry. However, although construction productivity is important in construction industry, gathering methodology and analyzing methodology of productivity data are not well-organized therefore productivity data is not utilized in the construction industry The purpose of this study is to develop productivity prediction system using data mining technology based on activities and to suggest frameworks about productivity data collection, accumulation.