• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.79-98
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• 2011

This paper proposes a semantic recommendation technique for a personalized e-commerce portal. Semantic recommendation is achieved by utilizing the attributes of products. The semantic similarity of the products is merged with the rating information of the products to provide an accurate recommendation. The recommendation technique also analyzes various attitudes of the customer to evaluate the implicit rating of products. Attitudes are classifies into three types such as "purchasing product", "adding product to shopping cart", and "viewing the product information." We implicitly track customer attitude to estimate the rating of products for recommending products. Also we implement a session validation process to identify the valid sessions that are highly important for giving an accurate recommendation. Our recommendation technique shows a high degree of accuracy as we use age groupings of customers with similar preferences. The experimental section shows that our proposed recommendation method outperforms well known collaborative filtering methods not only for the existing customer, but also for the new user with no previous purchase record.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.6
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• pp.79-94
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• 2018

The purpose of this study is to specify a probabilistic tracking mechanism for customer luxury purchase implemented by hidden Markov model, Bayesian inference, customer satisfaction and net promoter score. In this paper, we have designed a probabilistic model based on customer's actual data containing purchase or non-purchase states by tracking the SPC chain : customer satisfaction -> customer referral -> purchase/non-purchase. By applying hidden Markov model and Viterbi algorithm to marketing theory, we have developed the statistical model related to probability theories and have found the best purchase pattern scenario from customer's purchase records.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.299-305
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• 2021

This study examined to identify the factors influencing on inpatients' satisfaction with hospitalization and willingness to recommend hospital to others. Data from the 2018 National Patient Experience Survey were used for the analysis. Of the 593 patients experiencing inpatient services, multivariate linear regression analysis was conducted to explore the factors such as physician care, nursing care, facility and administrative support, and healthcare system on inpatients' satisfaction after controlling for their socio-demographic and health related factors. The study found that physician care, nursing care, administrative support and healthcare system were related to inpatients' satisfaction and willingness to recommend hospital. To improve inpatients' satisfaction, it is necessary to improve healthcare professionals' overall patient-centerdness attitude, user friendly hospital facilities and administrative support services and efforts to trust and satisfaction on healthcare system from the patients' perspectives.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.3
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• pp.5-26
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• 2022

The purpose of this study is to analyze high school students' understanding and use of the recommended books lists. The survey distributed to high school students in seven high schools located in Seoul, and 311 students responded. Using SPSS 24, the data was analyzed by frequency, binary logistic model, and one-way ANOVA. Results show the followings. First, the meaningful factors affecting students' use of recommended books lists are gender, grade levels, and the degree to which students think recommended books lists include the books that are suitable and interesting. Particularly, the degree to which students think recommended books lists include the suitable books for them is the strong factor affecting students' use of the recommended books lists. Second, male students are less likely to use recommended books lists than female students. Male students consistently are less likely to use the recommended books lists made by school librarians, subject teachers, and reading experts and/or organizations. Third, teacher-librarians believed that the recommended books lists would help students who do not enjoy reading and have difficulties in reading. However, the study finds that students who enjoy reading and read well are more willing to use the recommended books lists made by school librarians, subjects teachers, and reading experts and/or organizations than those who do not. Fourth, students are most willing to use the recommended books lists for college preparation. The findings suggest the further research topics in designing the recommended books lists suitable for high school students and in scaffolding the high school students' use of book information reflected in recommended books lists.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.173-184
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• 2018

This study was conducted to construct and test structural equation modeling of the causal relationship of job satisfaction of nursing staff with satisfaction, revisit intention and recommendation of the hospital by patients. The data utilized in this study were the second data acquired from the 2012 Public Hospital Evaluation Programme. The subjects of this study were 2,375 nursing staff and 3,433 patients at 39 district public hospitals. The instrument of job satisfaction of nursing staff consisted of five factors and 13 items. The instruments of satisfaction, revisit intention, and recommendation to others of patients consisted of one question on an 11 point scale (0: very negative, 10: very positive). The data were analyzed using SPSS version 20.0 and AMOS version 20.0. Model fit indices for the hypothetical model were suitable for the recommended level: model of in-patient ${\chi}^2$ 904.598 (df=81, p<0.001), GFI 0.938, AGFI 0.900, RMSR 0.076, mode of out-patient ${\chi}^2$ 869.021(df=81, p<0.001), GFI 0.940, AGFI 0.900, RMSR 0.074. In conclusion, nursing staff are the largest group in public hospitals, and they provide direct care to patients. Therefore, job satisfaction of nursing staff should be enhanced to improve satisfaction of patients because their attitude significantly influences patient satisfaction.

• Korean Journal of Construction Engineering and Management
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• v.11 no.6
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• pp.100-110
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• 2010

The main roots of CM service contracts include existing customer repurchases and those made by new customers by existing ones. The study on customers and loyalty can be factors to strengthen CM's competitiveness. However, there have been little attempt to study customer satisfaction and customer loyalty. Construction Management (CM), the advanced construction management method, was introduced 15 years ago in the mid 1990's in the domestic market. The aim of this research is to build a model that can predict customer loyalty based on how much customers are satisfied with CM service. To measure customer satisfaction and loyalty, this research surveyed 135 decision-makers who have experienced CM services. Customer satisfaction was tested and analyzed according to different phases: planning, designing, procurement, construction, and post construction. Referral intention was tested based on NPS theory. Customer types were divided into detractors, passively satisfied and promoters according to the tested measurement and multinomial logistic regression between the satisfaction by construction phases and customer types. This research resulted to a model that can predict customer types: detractors, passively satisfied and promoters, which were determined according to satisfaction level. The initial planning phase also revealed which factor is most influential for a customer to become promoter. These results can be used to acquire customer loyalty by managing the satisfaction of customers through a project under an Internet-based environment. Such can provide the needed information in quickly exploring positive and negative word-of-mouth feedbacks.

• 한국경영정보학회:학술대회논문집
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• 2007.11a
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• pp.591-596
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• 2007

본 연구에서는 상황 추론의 기능을 추천 시스템에 접목하였다. 연구의 대상 영역은 음악 추천 분야인데, 본 연구에서 제안하는 시스템은 세 개의 모듈, 즉 Intention Module, Mood Module 그리고 Recommendation Module로 구성되어 있다. Intention Module은 사용자가 음악을 청취할 의향이 있는지 없는지를 외부 환경의 상황 데이터를 이용하여 추론한다. Mood Module은 사용자의 상황에 적합한 음악의 장르를 추론한다. 마지막으로 Recommendation Module은 사용자에게 선정된 장르의 음악을 추천한다.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.152.2-152.2
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• 2010

기후변화, 석유자원 고갈 우려 등으로 인하여 그린에너지기술 개발에 대한 중요성은 크게 증가하고 있다. 그 가운데, 글로벌화된 경쟁구도 확대와 급속한 기술개발 속도로 인하여 국가간 또는 기업간 기술 개발 경쟁은 더욱 심해지고 있다. 이러한 상황하에서 그린에너지기술 개발을 위한 국제협력의 중요성은 더욱 증가하고 있다. 이에 각 국은 제도적, 경제적 지원을 통한 그린에너지기술 개발 및 국제협력을 적극 지원하고 있다. 그러나 우리나라의 경우 에너지기술 관련 R&D 예산 중 국제공동연구 비중은 0.6%로 선진국에 비해 지원 규모가 부족한 실정이며, 그린에너지기술 국제협력을 위한 기초 정보 역시 부족한 상황이다. 따라서 본 연구에서는 그린에너지기술 분야의 국외 선도 업체 및 기관을 대상으로 기술수준 및 협력의향을 조사하여 대외협력 맵을 구축하였다. 우선 '그린에너지 전략로드맵'상의 15대 기술 분류에서 상세 분석을 위한 주요 에너지기술을 선정하고 기술별 하위 전략품목별로 현황 조사를 실시하였다. 국내 전문가를 대상으로 1차, 2차 설문을 통하여 국제협력 추천 업체 및 기관, 기술수준을 조사하였으며, 조사된 국외 추천 선도 업체 및 기관을 대상으로 설문을 통하여 협력의향과 협력유형을 조사하였다. 조사된 자료를 통해 기술수준과 협력의향을 기준으로 4가지 유형으로 분류하여 대외협력 맵을 구성하고 구축된 대외협력 맵을 통해 국제협력 추진을 위한 시사점을 도출하였다.

• Smart Media Journal
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• v.13 no.1
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• pp.67-75
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• 2024

The purpose of this research is to investigate consumer responses to production recommendations by AI. In order to test hypotheses of this study, we conducted experimental study that was a 2(Brand reputation: high vs. low) X 2(Social comparison: high vs. low). The results of this study showed the interaction effects of brand reputation and social comparison on brand attitude. Based on the results, we provide theoretical implications to extent the existing research regarding product recommendations. Moreover, the results of this study provide some practical implications and a new aspect about AI recommendations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.2004-2012
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• 2010

This paper assess participant's satisfaction and referring will of embedding study- oriented TEC entrepreneurship program to drive policy implications for domestic entrepreneurship education, such as graduate schools of entrepreneurial management in Korea. The hypothesis test of this research shows that four assumptions given have been accepted among five of them as follows; education content, lecture style, prior knowledge variables with positively correlating to participant's satisfaction and referring will. In particular, the stronger highlights falls on algorithm approach with stressing on iterative and process oriented embedding study relating to education content, case-oriented lecture to lecture style and experience, customer understanding with business plan to prior knowledge.