• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.141-148
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• 2010

In mobile terminal recommend service system has general information restrictive recommend that individuality considering to user's information find and recommend. Also it has difficult of accurate information recommend bad points user's not offer individuality information preference recommend service. Therefore this paper is propose user's information individuality preference considering by user's individuality preference recommendation system using improved k-means algorithm. Propose method is correlation coefficients using user's information individuality preference when user's individuality preference recommendation using improved k-means algorithm. Restrictive information recommend to fix a problem, information of restrictive general recommend that user's information individuality preference offer to accurate information recommend. Performance experiment is existing service system as compared to evaluating the effectiveness of precision and recall, performance experiment result is appear to precision 85%, recall 68%.

• Journal of Society of Preventive Korean Medicine
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• v.26 no.2
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• pp.75-85
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• 2022

Objectives : The purpose of this study is to analyze the association between the satisfaction of Korean Medicine users and their intention to revisit and to recommend to others. Methods : This study conducted frequency analysis, chi-square test, and logistic regression analysis on 1,010 male and female Korean Medicine users aged 19 or higher in the country using data from the 2017 Korean Medicine Utilization and Herbal Medicine Consumption Survey. Results : The results of analyses revealed that the facilities in Korean Medicine clinics, the results of treatment, and the attitude of nurses and medical staff were the significant influencing factors on the intention to revisit and to recommend to others. Other than the above factors, the attitude toward medical treatment of Korean Medicine doctors and the satisfaction with an explanation of the treatment procedures were found to be important influencing factors on the intention to recommend to others. Conclusions : In order to increase the intention to revisit and to recommend to others a Korean Medicine clinics, the top priority lies in both proving high-quality medical services and promoting kind attitudes of medical staff.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.45-60
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• 2023

The purpose of this study is to explore factors that affect millennials and generation Z customers' perception on intention to recommend to use the digital payment services and invesetigate factors that affect perception on sustainable growth of the digital payment services. This study applied the following research questions: i) how perceived brand value, easy to use, personalization, open to public, and social value affect intention to recommend to use the digital payment services and ii) how perceived public policy, promotional strategy, and prspects affect intention to recommend to use the digital payment services to others. This study conducted an online survey. This study applied factor, ANOVA, and regression analysis to test hypotheses. The results of this study found that effects of personalization, open to public, and social value on intention to recommend the service showed significance in the case of millennials, while effects of brand value, easy to use, and open to publis on intention to recommend the service showed significance in the case of generation Z. The results provide managerial and policy implications on how to apply better strategies and pepare policies to enhance adoption of the digital payment service in cases of millennials and generation Z.

• Journal of Advanced Navigation Technology
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• v.18 no.5
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• pp.468-475
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• 2014

The recommend system is getting more difficult real time recommend by lager preference data set, computing power and recommend algorithm. For this reason, recommend system is proceeding actively one's studies toward distribute processing method of large preference data set. This paper studied distribute processing method of large preference data set using hadoop distribute processing platform and mahout machine learning library. The recommend algorithm is used Co-occurrence Matrix similar to item Collaborative Filtering. The Co-occurrence Matrix can do distribute processing by many node of hadoop cluster, and it needs many computation scale but can reduce computation scale by distribute processing. This paper has simplified distribute processing of co-occurrence matrix by changes over from four stage to three stage. As a result, this paper can reduce mapreduce job and can generate recommend file. And it has a fast processing speed, and reduce map output data.

• Journal of Distribution Science
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• v.18 no.2
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• pp.91-98
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• 2020

Purpose: This research aimed to suggest retailing companies some ways to enhance customer satisfaction with service recovery and recommendation intention towards these companies. For this purpose, current study examined the relationships among service recovery justice, service failure severity, customer trust, recovery satisfaction and intention to recommend and the moderating role of ego-resilience. Research design, data and methodology: Current study developed a structural equation model in which perceived service recovery justice is a predictor, service failure severity, customer trust, recovery satisfaction are mediators, intention to recommend is a dependent variable and the ego-resilience is a moderator between the perceived service recovery justice and the customer trust and the recovery satisfaction. Data were collected from customers who experienced service failures from retailers. A total of 400 questionnaires were collected and 365 samples were used for analysis after deleting data having missing value. SPSS 25.0 and AMOS 24.0 were used to test the validity, reliability, and structural equation modeling. Results: Empirical results showed that the perceived service recovery justice had a negative influence on the perceived service failure severity and a positive influence on the customer trust and the recovery satisfaction. These results indicate that when customers perceive the service recovery justice more highly, they perceive the service failure less severe but they perceive the retailer more trustworthy and are satisfied with service recovery. In addition, the customer trust and the recovery satisfaction had a positive influence on the intention to recommend. These results indicate that when customers perceive the retailer more trustworthy and are satisfied with service recovery, they are more intend to recommend the retailer. Moreover, the influence of the perceived service recovery justice on the customer trust and the recovery satisfaction was moderated by the ego-resilience. Conclusions: This study contributed to the service recovery literature by proving the relationship among service recovery justice, service failure severity, customer trust, recovery satisfaction and intention to recommend. Moreover, current research introduced the ego-resilience into service recovery research area and revealed the moderation role of the ego-resilience. Managerially, this research suggested retailing companies some ways to effectively recover from service failure.

• Nutrition Research and Practice
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• v.4 no.1
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• pp.75-81
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• 2010

This study explored the conceptual framework of dieticians' intentions to recommend functional food and the mediating role of consumption frequency. A web-based survey was designed using a self-administered questionnaire. A sample of Korean dieticians (N=233) responded to the questionnaire that included response efficacy, risk perception, consumption frequency, and recommendation intention for functional foods. A structural equation model was constructed to analyze the data. We found that response efficacy was positively related to frequency of consumption of functional foods and to recommendation intention. Consumption frequency also positively influenced recommendation intention. Risk perception had no direct influence on recommendation intention; however, the relationship was mediated completely by consumption frequency. Dieticians' consumption frequency and response efficacy were the crucial factors in recommending functional foods. Dieticians may perceive risks arising from the use of functional foods in general, but the perceived risks do not affect ratings describing dieticians' intentions to recommend them. The results also indicated that when dieticians more frequently consume functional foods, the expression of an intention to recommend functional foods may be controlled by the salience of past behaviors rather than by attitudes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.103-108
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• 2021

It is difficult to predict an increase or decrease of stock price because of uncertainty. Researches for prediction of stock price using AI technology have been done for a long time. Recently stock buy/sell recommend programs called by Robot Advisor using AI machine learning technology are used. In this paper, to develop a stock buy/sell recommend system using AI technology, an core engine of this system is designed. An analysis and design method of a stock buy/sell recommend system software using AI machine learning technology will be presented by showing user requirement analysis using object-oriented analysis method, flowchart and screen design.

• Journal of Society of Preventive Korean Medicine
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• v.27 no.3
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• pp.83-95
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• 2023

Objectives : The purpose of this study is to analyze the factors affecting the intention of chronic disease patients on revisiting and recommending those clinics to others. Methods : This study conducted the frequency analysis, Rao-scott chi-square test, and logistic regression analysis on 927 people, who answered that they had been diagnosed with a chronic disease, using data from the 2020 Korean Medicine Utilization and Herbal Medicine Consumption Survey. Results : The results of analyses revealed that the attitude of medical staff, and the treatment results were the significant influencing factors on the intention to revisit and to recommend to others. Other than the above factors, the medical expenses were found to be important influencing factors on the intention to recommend to others. Conclusions : In order to increase the intention to revisit and to recommend to others a Korean Medicine clinics, the top priority lies in both proving high-quality medical services and promoting friendly attitudes of medical staff. In addition, it is necessary to actively utilize korean medicine to guarantee patients' medical options.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.211-214
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• 2003

In this paper, we intend to find user's TV program choosing pattern and, recommend programs that he/she wants. So we suggest item dependency map which express relation between chosen program. Using an algorithm that we suggest, we can recommend an program, which a user has not saw yet but maybe is likely to interested in. Item dependency map is used as patterns for association in hopfield network so we can extract users global program choosing pattern only using users partial information. Hopfield network can extract global information from sub-information. Our algorithm can predict user's inclination and recommend an user necessary information.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.246-250
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• 2005

Recommand Systems are being used by an ever-increasing number of E-Commerce to help customers find products to purchase. Recommend Systems offer a technology that allows personalized recommendations of items of potential interest to users based on information about similarities and dissimilarities among different customers tastes. In this paper, we design and build a Recommend System using the historical customer movie purchase transactions and extracts the knowledge needed to make association recommendations to new customers.