• Title/Summary/Keyword: course recommendation

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A Study on the Influence of Choice Properties of Food Carving Decoration Lecture on Recommended Intention and Revisiting Intention

  • Kwag, Myung Sug;Kim, Jin Soo
    • Asia Pacific Journal of Business Review
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    • v.5 no.1
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    • pp.21-36
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    • 2020
  • This paper examines the effect of the choice properties of food carving decoration lectures on the recommendation and revisiting intention. As the culinary industry grows, consumers seek not only the value of satiety through food but also the value of aesthetics. They perceived satisfaction from the taste and appearance of the food as well as the interior of the restaurant and the service. Food carving is an important means of fulfilling consumer satisfaction value which is ever-changing. This study attempts to analyze the relationship between the choice properties of food carving lectures and the course recommendation and revisiting intention. This study hypothesis was formulated and the survey was conducted on 125 respondents who had experienced food carving lectures. The reliability and validity of measurement items were verified through Cronbach's Alpha and factor analysis. As a result, all measurement items showed no abnormality. The results of the analyses are as follows. The education satisfaction, education commitment, and brand image, the choice properties of food carving decoration lecture, were found to have a positive effect on the recommendation intention. The results also showed that the education commitment and brand image of food carving decoration lectures were positively associated with revisiting intention. Lastly, the implications of these findings were suggested and for future research were discussed.

A study on development method for practical use of Big Data related to recommendation to financial item (금융 상품 추천에 관련된 빅 데이터 활용을 위한 개발 방법)

  • Kim, Seok-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.8
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    • pp.73-81
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    • 2014
  • This study proposed development method for practical use techniques compromise data storage layer, data processing layer, data analysis layer, visualization layer. Data of storage, process, analysis of each phase can see visualization. After data process through Hadoop, the result visualize from Mahout. According to this course, we can capture several features of customer, we can choose recommendation of financial item on time. This study introduce background and problem of big data and discuss development method and case study that how to create big data has new business opportunity through financial item recommendation case.

A Collaborative Filtering-based Recommendation System with Relative Classification and Estimation Revision based on Time (상대적 분류 방법과 시간에 따른 평가값 보정을 적용한 협력적 필터링 기반 추천 시스템)

  • Lee, Se-Il;Lee, Sang-Yong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.2
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    • pp.189-194
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    • 2010
  • In the recommendation system that recommends services to a specific user by using the estimation value of other users for users' recommendation service, collaborative filtering methods are widely used. But such recommendation systems have problems that exact classification is not possible because a specific user is classified to already classified group in the course of clustering and inexact result can be recommended in case of big errors in users' estimation values. In this paper, in order to increase estimation accuracy, the researchers suggest a recommendation system that applies collaborative filtering after reclassifying on the basis of a specific user's classification items and then finding and correcting the estimation values of the users beyond the critical value of time. This system uses a method where a specific user is not classified to already classified group in the course of clustering but a group is reorganized on the basis of the specific user. In addition, the researchers correct estimation information by cutting off the subordinate 10% from the trimmed mean of samples and then applies weight over time to the remaining data. As the result of an experiment, the suggested method demonstrated about 14.9%'s more accurate estimation result in case of using MAE than general collaborative filtering method.

Artificial Intelligence-Based High School Course and University Major Recommendation System for Course-Related Career Exploration (교과 연계 진로 탐색을 위한 인공지능 기반 고교 선택교과 및 대학 학과 추천 시스템)

  • Baek, Jinheon;Kim, Hayeon;Kwon, Kiwon
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.1
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    • pp.35-44
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    • 2021
  • Recent advances in the 4th Industrial Revolution have accelerated the change of the working environment, such that the paradigm of education has been shifted in accordance with career education including the free semester system and the high school credit system. While the purpose of those systems is students' self-motivated career exploration, educational limitations for teachers and students exist due to the rapid change of the information on education. Also, education technology research to tackle these limitations is relatively insufficient. To this end, this study first defines three requirements that education technologies for the career education system should consider. Then, through data-driven artificial intelligence technology, this study proposes a data system and an artificial intelligence recommendation model that incorporates the topics for career exploration, courses, and majors in one scheme. Finally, this study demonstrates that the set-based artificial intelligence model shows satisfactory performances on recommending career education contents such as courses and majors, and further confirms that the actual application of this system in the educational field is acceptable.

Design and Implementation of a Mobile Course Coordinator System (모바일 코스 코디네이터 시스템의 설계 및 구현)

  • Lee, Youngseok;Cho, Jungwon;Han, Yongjae;Choi, Byung-Uk
    • The Journal of Korean Association of Computer Education
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    • v.8 no.5
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    • pp.51-62
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    • 2005
  • In the aspect of the faculty, a course coordinator plays an significant role in managing the curriculum and counseling students on academic matters and fostering their progress in the course. However, the course coordinator cannot afford to advise students on which fields of their faculty fit them and which courses they have to take. This paper proposes a mobile course coordinator system to help students learn courses of their major fields deeply. Also the proposed system is implemented by using WIPI technology, so that it is platform-independent and it is able to assist the course coordinator who is counseling students. And the students with personal cellular phones are able to keep tracking their courses, and improve their knowledge about major subjects by taking courses which the system's inference engine will advise.

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A Learner Tailoring Question Recommendation System for Web based Learning Evaluation System (웹 기반 학습평가를 위한 학습자 중심 문제추천 시스템)

  • Jeong, Hwa-Young;Kim, Eun-Won;Hong, Bong-Hwa
    • 전자공학회논문지 IE
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    • v.45 no.4
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    • pp.68-73
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    • 2008
  • In this research, we proposed a learner tailoring question recommendation system for web based learning evaluation system. For teaming evaluation process, this system used the item difficulty Each question was stored and managed to the question bank. Item difficulty was recalculated during teaming process and feedback in next course. For learner tailoring question recommendation, learner could choice the teaming part and set the learning difficulty. In application result of proposal method, almost learner could improve learning score by controling teaming difficulty.

A Study for Competency Enhancing of Creative Enterprise based on Textile Materials (텍스타일 기반 창조기업의 역량강화를 위한 교육평가 연구)

  • Yoon, Hae-Gyung;Choi, Seung-Bae
    • Journal of Fisheries and Marine Sciences Education
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    • v.27 no.2
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    • pp.452-466
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    • 2015
  • The study analyzed the result of a survey on educational programs after the provision of professional development education in textile-based industries, with the aim of suggesting a method of evaluating professional development education, by shedding new light on the educational contents and environment required by industries and on the components required to strengthen competence based on an evaluation of the outcomes of such educational programs. Methods of analysis included frequency & average analysis, ANOVA and portfolio analysis, and a questionnaire containing seven questions on satisfaction with 'educational contents,' six questions on satisfaction with 'educational environment,' three questions on educational effect and questions on overall satisfaction with education was used as an analysis tool. Data used in the analysis was obtained through a survey of the attendants of lectures given from January 2014 to September 2014, and the respondents included 30 persons enrolled in CEO courses, 167 persons enrolled in employment courses and 101 persons enrolled in employment & start-up business courses. The results of the research are as follows. 1. Looking at frequency distribution by educational course, it was shown, from highest to lowest, to be Incumbent Courses (167 persons, 56%), Employment & Start-up Courses (101 persons, 33.9%) and CEO Courses (30 persons, 10.1%). Looking at average analysis by question, the value of most questions on Employment & Start-up Courses turned out to be lower than Employment Courses and CEO Courses. 2. Through a variance analysis on questions related to educational courses (Employment & Start-up Course, Incumbent Course & CEO Course) and post-verification, it turned out that Employment Course is in the same group as the CEO Course in most questions, and that Employment & Start-up Course was a separate group. 3. Overall satisfaction with education turned out to be as high, at 4.1 out of 5. 4. Through a portfolio analysis on educational courses, it was found that 'Overall Satisfaction with Educational Contents,' 'Usefulness of Educational Contents,' 'Overall Satisfaction with Educational Environment' and 'Quality and Ability of Instructors' were included in areas of recommendation.

Case Study on Engineering Clinic Operation Based on Industry Needs (산업체 수요에 기반한 산업의료원 교과목 운영 사례)

  • Yu, Yun Seop
    • Journal of Practical Engineering Education
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    • v.6 no.1
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    • pp.51-55
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    • 2014
  • A case study on engineering clinic operation based on industry needs is introduced. Engineering clinic is a course that students and professor solve bottleneck techniques provided from an industry. The industry presents the bottleneck techniques to the professor and the professor plans a course that the students learn how to solve them, and the students train field adaptability by solving them. From the course evaluation of the engineering clinic, the students give high scores to the awareness of the course objectives, the performance period, the smooth communication, the application and understanding of major, the problem solving skill, the cooperation ability, the opportunity of carrier choice, and the course recommendation. Two semesters give higher satisfaction to the students than one semester because two semesters are long enough to solve the bottleneck techniques provided from the industry. It gives good opportunity that the students get a job through completing the course.

Design and Implementation of a Wine Recommendation Mobile Application (와인추천 모바일 어플리케이션 설계 및 구현)

  • Park, Si-Myung;Yoon, So-Young;Seo, Eun-Be;Son, Jong-Seo;Park, So-Hyun;Park, Young-Ho
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.2
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    • pp.79-88
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    • 2016
  • Recently, there is an increasing number of startups in wine business because of the rapid growth of wine consumption. The entrepreneurs need support to prepare infrastructure of wine business. Entrepreneurship is a course of preparing funding, personnel, and technology for preliminary entrepreneurs. In this paper, we implement a wine recommendation application for preliminary entrepreneurs of preparing the wine business as part of the technical support project. The proposed application is to collect accurate data using barcode recognition technology. Finally, proposed application aims the building of the wine knowledge-base through the data analysis by applying efficient algorithms.

A Development of Optimal Travel Course Recommendation System based on Altered TSP and Elasticsearch Algorithm (변형된 TSP 및 엘라스틱서치 알고리즘 기반의 최적 여행지 코스 추천 시스템 개발)

  • Kim, Jun-Yeong;Jo, Kyeong-Ho;Park, Jun;Jung, Se-Hoon;Sim, Chun-Bo
    • Journal of Korea Multimedia Society
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    • v.22 no.9
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    • pp.1108-1121
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    • 2019
  • As the quality and level of life rise, many people are doing search for various pieces of information about tourism. In addition, users prefer the search methods reflecting individual opinions such as SNS and blogs to the official websites of tourist destination. Many of previous studies focused on a recommendation system for tourist courses based on the GPS information and past travel records of users, but such a system was not capable of recommending the latest tourist trends. This study thus set out to collect and analyze the latest SNS data to recommend tourist destination of high interest among users. It also aimed to propose an altered TSP algorithm to recommend the optimal routes to the recommended destination within an area and a system to recommend the optimal tourist courses by applying the Elasticsearch engine. The altered TSP algorithm proposed in the study used the location information of users instead of Dijkstra's algorithm technique used in previous studies to select a certain tourist destination and allowed users to check the recommended courses for the entire tourist destination within an area, thus offering more diverse tourist destination recommendations than previous studies.