• Industry Promotion Research
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• v.9 no.3
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• pp.273-284
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• 2024

The objective of this thesis is to analyze the impact of transactional and transformational leadership styles on job performance. This research employs questionnaire surveys and statistical analysis to examine the relationships among the three variables. The subjects of this thesis are bank employees, and the survey was conducted using a random sampling method via online questionnaires. Data was statistically analyzed using SPSS 28.0, which included frequency analysis, reliability and validity analysis, correlation analysis, and regression analysis. The findings indicate that transformational leadership can significantly enhance job performance by encouraging innovation and boosting employee morale. Conversely, transactional leadership, with its excessive emphasis on rules and procedures and a strict reward and punishment system, may limit employees' innovative capabilities and reduce their satisfaction, thus negatively affecting job performance. This thesis contributes to understanding the impact of leadership styles on organizational effectiveness, advancing leadership theories, and providing theoretical support for organizational management decisions.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.877-884
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• 2011

The decision tree is a representative algorithm of data mining and used in many domains such as retail target marketing, fraud detection, data reduction, variable screening, category merging, etc. This method is most useful in classification problems, and to make predictions for a target group after dividing it into several small groups. When we create a model of decision tree with a large number of input variables, we suffer difficulties in exploration and analysis of the model because of complex trees. And we can often find some association exist between input variables by external variables despite of no intrinsic association. In this paper, we study on the removal method of unnecessary input variables using multiple external association rules. And then we apply the removal method to actual data for its efficiencies.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.1-17
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• 2010

Association rules among product items by association analysis suggest sales effect among products. These are useful for marketing strategies such as cross-selling and product display etc. However, if we evaluate more practical product values reflecting cross-selling effects, they will be also more useful for the decisions of companies such as product item selection for product assortment and profit maximization etc. This study proposes product value evaluation models with the concept of effective value based on single-item association chain and itemset association chain. In addition to that, we performed experiments with transaction data related to clothing of an online shopping mall in Korea to show the performances of our models. In result, we confirmed that some items increased in effective values compared with their pure values while the others decreased in effective values.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.189-199
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• 2017

Thisstudy quantitatively analyzed the research trendsin the use ofICT ofthe environmental field using the text mining technique. To that end, the study collected 359 papers published in the past two decades(1996-2015)from the National Digital Science Library (NDSL) using 38 environment-related keywords and 16 ICT-related keywords. It processed the natural languages of the environment and ICT fields in the papers and reorganized the classification system into the unit of corpus. It conducted the text mining analysis techniques of frequency analysis, keyword analysis and the association rule analysis of keywords, based on the above-mentioned keywords of the classification system. As a result, the frequency of the keywords of 'general environment' and 'climate' accounted for 77 % of the total proportion and the keywords of 'public convergence service' and 'industrial convergence service' in the ICT field took up approximately 30 % of the total proportion. According to the time series analysis, the researches using ICT in the environmental field rapidly increased over the past 5 years (2011-2015) and the number of such researches more than doubled compared to the past (1996-2010). Based on the environmental field with generated association rules among the keywords, it was identified that the keyword 'general environment' was using 16 ICT-based technologies and 'climate' was using 14 ICT-based technologies.

• Journal of Families and Better Life
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• v.25 no.1 s.85
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• pp.101-112
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• 2007

In this paper, 274 traditional fairy tales of South and North Korea were selected for research. The research was performed using a content analysis chart, and found differences in the number of characters, how ideology and social setting affect categorization of the characters, and what values are represented in the fairy tails of each country. Analysis of the general characteristics of traditional fairy tales of South and North Korea shows that South Korean traditional fairy tales have more cases where $1{\sim}4$ characters appear. In North Korean fairy tales, 5 or more characters generally appear. Analysis of the categories of characters in traditional fairy tales of South and North Korea found that characters fall into categories of family, friend and tutor, village, and the native country more often in South Korean fairy tales than in North Korean fairy tales. Character categorizations of county and foreign countries are found more often in North Korean fairy tales. In particular, the difference in character categorization of family, friend and tutor, and county shows that different ideology and social setting affected categories of characters. Research on traditional fairy tales of South and North Korea shows that traditional fairy tales of South Korea have chosen self-respect, self-restraint, fidelity(responsibility), understanding others, manners and honesty as themes more often than those of North Korea and subjects such as frugality, sharing, order and rules, cooperation and patriotism(ecosystem protection) we found more often in those of North Korea.

• Journal of Korea Multimedia Society
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• v.6 no.5
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• pp.909-920
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• 2003

Nowadays, IT for CRM has been growing and developed rapidly. Typical techniques are statistical analysis tools, on-line multidimensional analytical processing (OLAP) tools, and data mining algorithms (such neural networks, decision trees, and association rules). Among customer data, web log data is very important and to use these data efficiently, applying OLAP technology to analyze multi-dimensionally. To make OLAP cube, we have to precalculate multidimensional summary results in order to get fast response. But as the number of dimensions and sparse cells increases, data explosion occurs seriously and the performance of OLAP decreases. In this paper, we presented why the web log data sparsity occurs and then what kinds of sparsity patterns generate in the two and t.he three dimensions for OLAP. Based on this research, we set up the multidimensional data models and query models for benchmark with each sparsity patterns. Finally, we evaluated the performance of three OLAP systems (MS SQL 2000 Analysis Service, Oracle Express and C-MOLAP).

• Journal of Platform Technology
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• v.12 no.3
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• pp.3-15
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• 2024

Knowledge mining is a research field that applies various techniques such as data modeling, information extraction, analysis, visualization, and result interpretation to find valuable knowledge from diverse large datasets. It plays a crucial role in transforming raw data into useful knowledge across various domains like business, healthcare, and scientific research etc. In this paper, we propose analytical techniques for performing knowledge discovery and data mining from various data by extending the Formal Concept Analysis method. It defines algorithms for representing diverse formats and structures of the data to be analyzed, including models such as many-valued data table data and triadic data table, as well as algorithms for data processing (dyadic scaling and flattening) and the construction of concept hierarchies and the extraction of association rules. The usefulness of the proposed technique is empirically demonstrated by conducting experiments applying the proposed method to public open data.

• The KIPS Transactions:PartC
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• v.11C no.4
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• pp.455-462
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• 2004

Network attacks are various types with development of internet and are a new types. The existing intrusion detection systems need a lot of efforts and costs in order to detect and respond to unknown or modified attacks because of detection based on signatures of known attacks. In this paper, we present a design and implementation for mining prototype system to predict unknown or modified attacks through network protocol attributes analysis. In order to analyze attributes of network protocols, we use the association rule and the frequent episode. The collected network protocols are storing schema of TCP, UDP, ICMP and integrated type. We are generating rules that can predict the types of network attacks. Our mining prototype in the intrusion detection system aspect is useful for response against new attacks as extra tool.

• Journal of Korean Association for Spatial Structures
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• v.11 no.3
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• pp.125-135
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• 2011

This study presents the shape creation process using L-system model of morphogenesis technique. In general, L-system model has been applied to represent the visualization of biological plant. But, this study proposes the shape generation process of L-system model to apply the architectural field. The L-system model consists of two parts such as string generation step and string analysis step. The string generation step shows the process for a string rewriting. This step requires alphabet, axiom and rules to generate a string. Also, the string analysis step gives the meaning in string to generate various forms. Especially, through the various application examples, we can find out the shape creation models for the space structures.

• Journal of the Korea Fashion and Costume Design Association
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• v.8 no.3
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• pp.119-128
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• 2006

The augmentation in social deviation of adolescence is one of the issues that modern society should resolve. Deviation behavior of adolescents is often expressed as clothing behavior being against the social or school rules. Therefore, to understand the social deviation and clothing behavior of adolescents, the study investigated the relationship with the level of social deviation, clothing interest, the attitude toward clothing, and clothing deviation. Survey was utilized to collect the data and subjects were 411 female high school students. Principal component analysis and regression analysis were used to analyze the data. While the level of social deviation of female high school students had no statistically significant influence on the fashion-oriented attitude, clothing interest of them had an effect on the fashion-oriented attitude, suggesting that adolescents, having a high interest in clothing, thought the fashion-oriented attitude as an important clothing attribute. The level of social deviation of subjects had a statistically significant influence on the behavior of clothing deviation. The less the subjects took an interest in clothing and the lower the level of social deviation was, the more they thought the status-oriented clothing attitude as an important clothing attribute. Also, the result revealed a similar tendency in the modesty-oriented clothing attitude to that in the status-oriented clothing attitude.