• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.115-126
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• 2000

In General, data mining is defined as the knowledge discovery or extracting hidden necessary information from large databases. Its technique can be applied into decision making, prediction, and information analysis through analyzing of relationship and pattern among data. One of the most important works is to find association rules in data mining. Association Rule is mainly being used in basket analysis. In addition, it has been used in the analysis of web-log and user-pattern. This paper provides the application method in the field of marketing through the analysis of data using association rule as a technique of data mining.

• Journal of Korean Society for Quality Management
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• v.49 no.1
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• pp.81-95
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• 2021

Purpose: The purpose of this study was to analysis pattern of nonconforming farmers who is one of the factors of unconformity in residual pesticides. Methods: Pattern analysis of nonconforming farmers were analyzed through convergence of safety data and farmer's DB data. Exploratory data analysis and association rule analysis were used for extracting factors related to unconformity. Results: The results of this study are as follows; regarding the exploratory data analysis, it was found that factors of farmers influencing unconformity in residual pesticides by total 9 factors; sampling time, gender, age, cultivation region, farming career, agricultural start form, type of agriculture, cultivation area, classification of agricultural products. Regarding the association rule analysis, non-conformity association rules were found over the past three years. There was a difference in the pattern of nonconforming farmers depending on the cultivation period. Conclusion: Exploratory data analysis and association rule analysis will be useful tools to establish more efficient and economical safety management plan for agricultural products.

• The Journal of the Korea Contents Association
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• v.16 no.6
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• pp.94-102
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• 2016

The purpose of this study was to investigate the effect of corporate association of sports equipment companies on brand trust, and brand loyalty. The subjects were college student and 400 data were collected and 385 of them were chosen as for final data analysis. Data analysis were conducted using frequency analysis, confirmatory factor analysis, reliability analysis, correlation analysis and structural equation modeling with SPSS 22.0 and AMOS 22.0. Based on the above study method and procedures, the results of the study are summarized as follows: First, corporate ability association and corporate social responsibility association had a positive effect on brand trust. Second, brand trust had a positive effect on brand loyalty.

• Journal of the Korea Fashion and Costume Design Association
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• v.17 no.1
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• pp.155-166
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• 2015

Based on marketing theories of brand and corporate association, and the social psychological theory of identity, the effects of the corporate brand on individual brand loyalty were established via two major routes. The empirical study is based on the response of 330 subjects who participated in a field survey. In the statistical analysis, Correlation Analysis, Factor Analysis, Sequential Equation Model Analysis were used for verification. The corporate association affected the formation of individual brand loyalty both the product level and corporate level. Specifically, the two types of brand response did differ in terms of their strength on brand loyalty. The present study contributes to the academic literature in that it disentangles the construct of the corporate brand from that of the individual brand and investigates the structural relations between the two.

• Journal of the Korean Home Economics Association
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• v.47 no.10
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• pp.87-95
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• 2009

This study conducted a content analysis of the treatises published in JKHEA(Journal of the Korean Home Economics Association). In total, 2,136 articles published in JKHEA from 1995 to the first half of 2009 were reviewed. Articles were classified by subject matters, research methods, number of researchers, presence of research fund, language and number of reference. Although it is useful to employ content analysis in reviewing academic articles on human ecology in all journal publications, the sheer size of literature available makes this task nearly impossible. As such, we have chosen JKHEA as a popular representative journal on human ecology. This study presented the empirical results of research trends and other characteristics in JKHEA. As such, the results of this study presented a snapshot analysis of research on human ecology and future trends.

• The Journal of Society for e-Business Studies
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• v.4 no.1
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• pp.21-36
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• 1999

Using user monitoring techniques on web, marketing decision makers in cyber shopping malls can gather customer behavior data as well as sales transaction data and customer profiles. In this paper, we present a marketing rule extraction technique for customer behavior analysis in cyber shopping malls, The technique is an application of market basket analysis which is a representative data mining technique for extracting association rules. The market basket analysis technique is applied on a customer behavior log table, which provide association rules about web pages in a cyber shopping mall. The extracted association rules can be used for mall layout design, product packaging, web page link design, and product recommendation. A prototype cyber shopping mall with customer monitoring features and a customer behavior analysis algorithm is implemented using Java Web Server, Servlet, JDBC(Java Database Connectivity), and relational database on windows NT.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.4
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• pp.249-255
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• 2016

Recently, transaction data is accumulated everywhere very rapidly. Association analysis methods are usually applied to analyze transaction data, but the methods have several problems. For example, these methods can only consider one-way relations among items and cannot reflect domain knowledge into analysis process. In order to overcome defect of association analysis methods, we suggest a transaction data analysis method based on probabilistic graphical model (PGM) in this study. The method we suggest has several advantages as compared with association analysis methods. For example, this method has a high flexibility, and can give a solution to various probability problems regarding the transaction data with relationships among items.

• Journal of Distribution Science
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• v.21 no.4
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• pp.121-129
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• 2023

Purpose: Market basket analysis is one of the most frequently used methods in the retail industry today as a technique to discover the product association. It is empirically analyzed how these product associations differ regionally in the case of the United States. Research design, data, and methodology: Based on the purchasing data of consumer panels collected from 49 US states, the association rules for each state was extracted with the corresponding lift values indicating product association. The difference in lift values in 49 states by the association rule was compared and tested for 49 states and for 4 census regions (Northeast, Midwest, South, West). Results: The association rules of 3/4 of the same association rules show positive associations or negative associations depending on the lift values of the states. There were significant differences in the lift values for 49 states, and for 4 census regions. These significant differences in the lift values were found to be related to the distance between states and whether states belong to the same census region. Conclusions: Retail product associations shown by market basket analysis may vary depending on regional distance or regional heterogeneity. It is necessary to pay attention to these points in multi-store environment.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.11
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• pp.5817-5821
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• 2012

Background/Aims: Glutathione S-transferase M1 (GSTM1) is a multifunctional enzyme that plays a critical role in the detoxification of varieties of carcinogenic metabolites. Many studies have been conducted to investigate the association between GSTM1 polymorphism and nasopharyngeal cancer (NPC) risk, but the findings among those studies are inconsistent. To assess this relationship more precisely, we performed a meta-analysis of all available studies on the subject. Methods: Case-control studies were identified by searching Pubmed, Embase, ISI Web of Science, and Wanfang databases through September 6, 2012. We used the pooled odds ratio (OR) with its corresponding 95% confidence interval (95%CI) to evaluate the association of GSTM1 polymorphism with NPC susceptibility. Subgroup analyses by pathological types, sex and smoking status were performed to further identify the association. Results: Overall, 11 published studies with 1,513 cases and 2,802 controls were finally included into this meta-analysis according to the inclusion criteria. Meta-analysis of total studies showed that the null genotype of GSTM1 was significantly associated with increased risk of NPC, when comparing with the non-null genotype (OR=1.51, 95%CI=1.33-1.72, POR<0.001). The association was still statistically significant in subgroup analysis of patients with nasopharyngeal squamous cell carcinoma (OR=1.73, 95%CI=1.24-2.42, POR=0.001). Males with the null genotype of GSTM1 were more likely to subject to NPC than females. In addition, the association between the null genotype of GSTM1 and NPC risk was strongest in individuals with exposure to smoking. Sensitivity analysis by sequential omission of any individual studies one at a time further demonstrated the significant association. Conclusions: The findings suggest that the null genotype of GSTM1 is a risk factor for NPC, and there is a gene-smoking interaction in this association.

• The Journal of the Korean dental association
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• v.40 no.5 s.396
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• pp.373-379
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• 2002