• Journal of the Korea Computer Industry Society
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• v.2 no.9
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• pp.1175-1182
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• 2001

One to one Marketing (a.k.a. database marketing or relationship marketing) is one of the many fields that will benefit from the electronic revolution and shifts in consumer sales and advertising. As a component of intelligent customer services on Internet storefront, this paper describes technology of providing personalized advertisement using the market basket analysis, a well-Known data mining technique. The underlining theories of recommendation techniques are statistics, data mining, artificial intelligence, and/or rule-based matching. In the rule-based approach for personalized recommendation, marketing rules for personalization are usually collected from marketing experts and are used to inference with customer's data. However, it is difficult to extract marketing rules from marketing experts, and also difficult to validate and to maintain the constructed Knowledge base. In this paper, using marketing basket analysis technique, marketing rules for cross sales are extracted, and are used to provide personalized advertisement selection when a customer visits in an Internet store.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.56-67
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• 2019

The aim of this study is to develop Artificial Intelligence (AI) based business models of media firms. We define AI and discuss 'AI activity model'. The practices of the efficiency model are home equipment-based personalization and media content recommendation. The practices of the expert model are media content commissioning, content rights negotiation, copyright infringement, and promotion. The practices of the effectiveness model are photo & video auto-tagging and auto subtitling & simultaneous translation. The practices of the innovation model are content script creation and metadata management. The related use cases from 2012 to 2017 are introduced along the four activity models of AI. In conclusion, we propose for media companies to fully utilize the AI for transforming from traditional to successful digital media firms.

• International Journal of Advanced Culture Technology
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• v.5 no.2
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• pp.82-89
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• 2017

The range of problems that can be handled by the activation of big data and the development of hardware has been rapidly expanded and machine learning such as deep learning has become a very versatile technology. In this paper, mnist data set is used as experimental data, and the Cross Entropy function is used as a loss model for evaluating the efficiency of machine learning, and the value of the loss function in the steepest descent method is We applied the GradientDescentOptimize algorithm to minimize and updated weight and bias via backpropagation. In this way we analyze optimal reliability value corresponding to the number of exercises and optimal reliability value without overfitting. And comparing the overfitting time according to the number of data changes based on the number of training times, when the training frequency was 1110 times, we obtained the result of 92%, which is the optimal reliability value without overfitting.

• International journal of advanced smart convergence
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• v.6 no.1
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• pp.39-43
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• 2017

As the industry grows, the amount of data grows exponentially, and data analysis using these serves as a predictable solution. As data size increases and processing speed increases, it has begun to be applied to new fields by combining artificial intelligence technology as well as simple big data analysis. In this paper, we propose a method to quickly apply a machine learning based algorithm through efficient resource allocation. The proposed algorithm allocates memory for each attribute. Learning Distinct of Attribute and allocating the right memory. In order to compare the performance of the proposed algorithm, we compared it with the existing K-means algorithm. As a result of measuring the execution time, the speed was improved.

• Korean Journal of Artificial Intelligence
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• v.8 no.1
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• pp.7-9
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• 2020

In this paper, a study was conducted to find a self-diagnosis method to prevent the spread of COVID-19 based on machine learning. COVID-19 is an infectious disease caused by a newly discovered coronavirus. According to WHO(World Health Organization)'s situation report published on May 18th, 2020, COVID-19 has already affected 4,600,000 cases and 310,000 deaths globally and still increasing. The most severe problem of COVID-19 virus is that it spreads primarily through droplets of saliva or discharge from the nose when an infected person coughs or sneezes, which occurs in everyday life. And also, at this time, there are no specific vaccines or treatments for COVID-19. Because of the secure diffusion method and the absence of a vaccine, it is essential to self-diagnose or do a self-diagnosis questionnaire whenever possible. But self-diagnosing has too many questions, and ambiguous standards also take time. Therefore, in this study, using SVM(Support Vector Machine), Decision Tree and correlation analysis found two vital factors to predict the infection of the COVID-19 virus with an accuracy of 80%. Applying the result proposed in this paper, people can self-diagnose quickly to prevent COVID-19 and further prevent the spread of COVID-19.

• Journal of Global Scholars of Marketing Science
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• v.9
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• pp.19-46
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• 2002

Market orientation emphasizes the capability of a firm to learn customers, competitors, and inter-functional coordination and to use this market intelligence of creating superior value in the marketplace. It has been proved that market orientation contributes to organizational performance. But the question is what the antecedents and consequent to superior market orientation are. The objective of this study is to assess the relationship between internal marketing and market orientation. In this study, Internal marketing consists of empowerment, internal communication, reward system, management supports, and education and training. The effects of internal marketing on market orientation were analysed by Structural equation model. Market orientation was positive affected by internal marketing, directly and indirectly. Specially, the management supports of internal marketing' constructs had relatively important effect on market orientation.

• Culinary science and hospitality research
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• v.23 no.8
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• pp.145-152
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• 2017

This study was performed to verify the importance of emotional aspect for hotel employees to derive the organizational commitment and customer orientation. Present study estimated the emotional intelligence as four factors: self emotion, other emotion, emotional utilization, and emotional regulation. Online survey method was used and distributed the questionnaires to hotel employees who are working for restaurants. A total of 300 questionnaires were distributed and 257 participants were employed for statistical analysis using SPSS 21.0 and AMOS 21.0 for Windows. As results, two factors(emotional utilization and emotional regulation) were significant antecedents of organizational commitment, and three factors(self emotion, other emotion, and emotional utilization) were critical predictors of customer orientation. In addition, organizational commitment has significantly influenced the customer orientation. According to the results of this study, hotel restaurant managers or hotel company need to understand the importance of the emotional intelligence for providing better service to their customers as well as improving the organizational commitment. These results will contribute to develop advanced marketing strategics for hotel restaurants employees who have many connections with customers in a hotel.

• Korean Journal of Artificial Intelligence
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• v.7 no.2
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• pp.13-17
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• 2019

Currently, the sports market continues to grow every year, and among them, professional baseball's entry income is larger than the rest of the professional league. In sports, strategies are used differently in different situations, and the analysis is based on data to decide which direction to implement. There is a part that a person misses in an analysis, and there is a possibility of a false analysis by subjective judgment. So, if this data analysis is done through artificial intelligence, the objective analysis is possible, and the strategy can be more rationalized, which helps to win the game. The most popular baseball to be applied to artificial intelligence to analyze athletes' strengths and weaknesses and then efficiently establish strategies to ease the competition. The data applied to the experiment were provided on the KBO official website, and the algorithms for forecasting applied linear regression. The results showed that the accuracy was 87%, and the standard error was ±5. Although the results of the experiment were not enough data, it would be possible to effectively use baseball strategies and predict the results of the game if the amount of data and regular data can be applied in the future.

• Journal of Platform Technology
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• v.10 no.1
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• pp.20-28
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• 2022

Artificial intelligence-based health data verification has become an essential element not only to help clinical research, but also to develop new treatments. Since the US Food and Drug Administration (FDA) approved the marketing of medical devices that detect mild abnormal diabetic retinopathy in adult diabetic patients using artificial intelligence in the field of medical diagnosis, tests using artificial intelligence have been increasing. In this study, an artificial intelligence model based on image classification was created using a Teachable Machine supported by Google, and a predictive model was completed through learning. This not only facilitates the early detection of cataracts among eye diseases occurring among patients with chronic diseases, but also serves as basic research for developing a digital personal health healthcare app for eye disease prevention as a healthcare program for eye health.

• The Journal of Economics, Marketing and Management
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• v.5 no.2
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• pp.1-9
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• 2017

This study has reviewed the "A survey on the relation between the employees' viewpoint with knowledge management and cultural intelligence among the employees working in Social Security Organization of Ardabil". The present study is functional in terms of objective and the method is descriptive and survey. This has asked the others' ideas and viewpoints concerning a specific subject and has analyzed them. About the nature and the method used, the present research is of correlation research. The population applied in this research includes all employees working in Social Security Organization of Ardabil consisting of 400. The method used for sampling is simple random sampling. To collect the information in the first step of the research the library method has been used. In this research the data has been collected through standard questionnaires. Then, via descriptive and inferential statistics the research data has been characterized and regarding the spatial scaling of the measurement to test the hypothesis the, correlation analysis of Pearson has been used and also to specify the reliability of the questionnaire the Chronbach's Alpha has been taken in use and the SPSS software to analyze the data also. The findings resulted from the study showed that there is a significant relation between the factors concerning employees' efficiency with knowledge management and the cultural intelligence and all hypotheses was confirmed.