• Title/Summary/Keyword: group recommendation

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Implementation of Demo Program for Visual Communication in Compliance with MPEG-21 Part 22: User Description (MPEG-UD 표준을 준수하는 비쥬얼 커뮤니케이션 데모 프로그램 개발)

  • Lim, Hea-Jin;Choi, Jang-Sik;Jeon, Jin-Young;Byun, Hyung-Gi
    • Journal of Sensor Science and Technology
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    • v.25 no.4
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    • pp.297-301
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    • 2016
  • ISO/IEC JTC1/SC29WG11 MPEG has been standardizing UD(user description) to give a user personalized recommendation services. Besides, CD(context description), service description(SD), and recommendation description(RD) are recently being standardized by UD Adhoc Group in MPEG with an advanced UD to cope with needs of current and upcoming services such as augmented reality and social network. The descriptions was reflected to MPEG-UD WD(Working Draft) at MPEG $107^{th}$ meeting and the document was finally approved as international standard by national bodies with standard number(ISO/IEC IS 21000-22 UD) at $114^{th}$ MPEG meeting. In addition, reference software WD to validate conformance of UD standard was approved at $113^{th}$ MPEG meeting. In this paper, we developed a demo program for visual communication according to guideline defined in reference software WD to validate the reference software as well as UD standard.

Blog Intelligence (블로그 인텔리전스)

  • Kim, Jae-Kyeong;Kim, Hyea-Kyeong;O, Hyouk
    • Journal of Information Technology Services
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    • v.7 no.3
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    • pp.71-85
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    • 2008
  • The rapid growth of blog has caused information overload where bloggers in the virtual community space are no longer able to effectively choose the blogs they are exposed to. Recommender systems have been widely advocated as a way of coping with the problem of information overload in e-business environment. Collaborative Filtering (CF) is the most successful recommendation method to date and used in many of the recommender systems. In this research, we propose a CF-based recommender system for bloggers to find their similar bloggers or preferable virtual community without burdensome search effort. For such a purpose, we apply the "Interest Value" to CF recommender systems. The Interest Value is the quantity value about users' transaction data in virtual community, and can measure the opinion of users accurately. Based on the Interest Value, the neighborhood group is generated, and virtual community list is recommended using the Community Likeness Score (ClS). Our experimental results upon real data of Korean Blog site show that the methodology is capable of dealing with the information overload issue in virtual community space. And Interest Value is proved to have the potential to meet the challenge of recommendation methodologies in virtual community space.

Clothing Purchase Motives and Post-Purchase Dissatisfaction of Women (여성의 의복구매동기와 구매 후 불만족에 관한 연구)

  • 엄경은
    • Journal of the Korean Home Economics Association
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    • v.33 no.4
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    • pp.315-327
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    • 1995
  • The objective of this study were to classify the contents of clothing purchase motives and to examine the differences in post-purchase dissatisfaction and satisfaction of clothing according to the clothing purchase motives. Questionnaire was comprised of 36 Likert type items of clothing purchase motive measure, 15 items of post-purchase clothing dissatisfaction measure, and 1 item of satisfaction measures. Samples were 492 women in Incheon, Korean ; 279 were college students and 213 were housewives. The data were analyzed using factor analysis, cluster analysis, one-way ANOVA, Duncan's multiple range test, and χ2-test. The results of the study were the followings : 1. Subjects perceived 'becomingness' to be the most important motive, 'attractiveness of color' the second important, and 'salesperson's recommendation' the least. 2. 6 factors of clothing purchase motives were derived by factor analysis : F.1 'clothing utility and deficiency' ; F.2 'clothing quality' ; F.3 'financial frugality'. 3. Subjects were classified into the three motive groups by cluster analysis of the 6 factors : G.1 'the clothing appearance and others' influence' ; G.2 'the clothing quality and deficiency' ; G.3 'the motiveless'. 4. More college women were distributed in clothing appearance and others' influence group than housewives, while more housewives were distributed in clothing quality and deficiency group. 5. The clothing appearance and others' influence group expressed the highest post-purchase dissatisfaction and the lowest post-purchase satisfaction. The clothing quality and deficiency group expressed the highest post-purchase satisfaction, and the motiveless group expressed the lowest post-purchase dissatisfaction.

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Personalized Expert-Based Recommendation (개인화된 전문가 그룹을 활용한 추천 시스템)

  • Chung, Yeounoh;Lee, Sungwoo;Lee, Jee-Hyong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.1
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    • pp.7-11
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    • 2013
  • Taking experts' knowledge to recommend items has shown some promising results in recommender system research. In order to improve the performance of the existing recommendation algorithms, previous researches on expert-based recommender systems have exploited the knowledge of a common expert group for all users. In this paper, we study a problem of identifying personalized experts within a user group, assuming each user needs different kinds and levels of expert help. To demonstrate this idea, we present a framework for using Support Vector Machine (SVM) to find varying expert groups for users; it is shown in an experiment that the proposed SVM approach can identify personalized experts, and that the person-alized expert-based collaborative filtering (CF) can yield better results than k-Nearest Neighbor (kNN) algorithm.

Eliciting stated preferences for drugs reimbursement decision criteria in South Korea (선택실험법을 이용한 의약품 급여결정기준에 대한 선호분석)

  • Lim, Min-Kyoung;Bae, Eun-Young
    • Health Policy and Management
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    • v.19 no.4
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    • pp.98-120
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    • 2009
  • The purpose of this study is to elicit preference for drug listing decision criteria and to estimate the ICER threshold in South Korea using the discrete choice experiment (DCE) method. To collect the data, a DCE survey was administered to a subject sample either educated in the principle concepts of pharmacoeconomics or were decision makers within that field. Subjects chose between alternative drug profiles differing in four attributes: ICER, uncertainty, budget impact and severity of disease. The orthogonal and balanced designs were determined through computer algorithm to take the optimal set of drug profiles. The survey employed 15 hypothetical choice sets. A random effect probit model was used to analyze the relative importance of attributes and the probabilities of a recommendation response. Parameter estimates from the models indicated that three attributes (ICER, Impact, Severity of disease) influenced respondents' choice significantly(p${\pm}$0.001). In addition, each parameter displayed an expected sign. The Lower the ICER, the higher the probability of choosing that alternative. Respondents also preferred low levels of uncertainty and smaller impact on health service budget. They were also more likely to choose drugs for serious diseases rather than mild or moderate ones. Uncertainty however is not statistically significant. The ICER threshold, at which the probability of a recommendation was 0.5, was 29,000,000 KW/QALY in expert group and 46,500,000 KW/QALY in industry group. We also found that those in our sample were willing to accept high ICER to get medication for severe diseases. This study demonstrates that the cost-effectiveness, budget impact and severity of disease are the main reimbursement decision criteria in South Korea, and that DCE can be a useful tool in analyzing the decision making process where a variety of factors are considered and prioritized.

Empirical Study and Evaluation of Case-Based Learning for Improvement of Learning Outcome (학습 성과 개선을 위한 사례기반 학습의 실험적 연구 및 평가)

  • Kim, Seong-Kee;Kim, Young-Hak;Yoon, Hyeon-Ju
    • The Journal of Korean Association of Computer Education
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    • v.14 no.6
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    • pp.53-64
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    • 2011
  • This paper proposes and evaluates empirically a new recommendation method in order to improve the learning achievement of learners using case-based method. In this paper, we first carried out a survey targeting teachers who work currently in Gyeongbuk area, and constructed learning cases depending on critical factors of learning. We next recommended differentiated learning methods to learners classifying according to learning cases by achievement level through this survey. The students of a middle school took part in the experiment in order to evaluate empirically the proposed learning cases. The students were divided into three groups by their achievement level and three separate learning cases were applied to each group. The weights among learning improvement elements applying to each group were added through the survey result of teachers. The experiment using the proposed case-based recommendation method showed that the learning achievement of learners is improved considerably compared to the previous one.

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A Study on the Factors that Influence Consumers when Purchasing or Renting Hanbok (소비자가 한복구매 및 대여시 중점을 두는 요인에 관한 연구)

  • You, Hyo Soon;Jung, Mi Young
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.1
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    • pp.74-79
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    • 2013
  • The purpose of this study is to identify the factors that influence consumers when they purchase or rent Hanbok. We investigated the factors which affect consumers buying Hanbok, out of expectation that the rising interest in Hanbok caused by diversification of design and other various reasons would have a positive impact on purchases. Reflecting the increase of consumers renting Hanbok in the study, we also analyzed the factors that have an influence on rentals and compared the determinants of purchasing Hanbok and that of renting it. It turned out that consumers are mainly influenced by design, popular colors they prefer, and recommendation of clerks or friends. Through the comparison, we discovered that the purchasing group is more influenced by design while the renting group is more influenced by recommendation of friends and clerks. This result suggests that it would be an effective marketing strategy for shops to strengthen competitiveness by diversifing design of Hanbok, and for rental shops to do so by placing professional salesperson.

On the Determination of Outpatient's Revisit using Data Mining (데이터 마이닝을 활용한 병원 재방문도 영향요인 분석 : 외래환자의 만족도를 중심으로)

  • 이견직
    • Health Policy and Management
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    • v.13 no.3
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    • pp.21-34
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    • 2003
  • Patient revisit to used hospital is a key factor in determining a health care organization's competitive advantage and survival. This article examines the relationship between customer's satisfaction and his/her revisit associated with three different methods which are the Chi Square Automatic Interaction Detection(CHAID) for segmenting the outpatient group, logistic regression and neural networks for addressing the outpatient's revisit. The main findings indicate that the important factors on outpatient's revisit are physician's kindness, nurse's skill, overall level of satisfaction, hospital reputation, recommendation, level of diagnoses and outpatient's age. Among these ones, physician's kindness is the most important factor as guidelines for decision of their revisit. The decision maker of hospital should select the strategy containing the variable amount of the level of revisit and size of outpatient's group under the constraint on the hospital's time, budget and manpower given. Finally, this study shows that neural networks, as non-parametric technique, appear to more correctly predict revisit than does logistic regression as a parametric estimation technique.

Development of Collaborative Filtering Agent System for Automatic Recommendation (자동화된 추천을 위한 협동적 필터링 에이전트 시스템의 개발)

  • Hwang, Byung-Yeon;Kim, Eui-Chan
    • Proceedings of the Korea Information Processing Society Conference
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    • 2000.10a
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    • pp.473-476
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    • 2000
  • 최근 전자상거래에서 에이전트 기술들이 많이 나타나고 있는데, 주목해야 할 것은 패키지 형태로 내장될 수 있는 에이전트이다. 전자상거래 솔루션에 탑재되어 자동화시킨 에이전트로서 NetPerception 의 GroupLens 엔진과 MacroMedia의 LikeMinds가 있는데 이들은 협동적 필터링을 구현한 것들이다. 현재 이러한 협동적 필터링 에이전트 시스템이 탑재된 전자상거래 솔루션들이 등장하고 있다. 하지만 add-on 성격이 부족하고, 실제 협동적 필터링 알고리즘에 의해 고객의 취향이나 기호에 맞는 아이템을 추천하는 진정한 의미의 에이전트 시스템은 찾아보기 힘들다. 그래서, 이러한 점을 보완한 MindReader 시스템을 개발하였다. 제안된 알고리즘은 기존의 GroupLens 알고리즘에 클러스터링을 접목시킨 알고리즘을 사용하였다.

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Factors affecting Organic Food Purchasing Decisions of Kindergartens in Ho Chi Minh City

  • TRUONG, Thi Hong;NGUYEN, Xuan Truong
    • Journal of Distribution Science
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    • v.18 no.7
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    • pp.73-81
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    • 2020
  • Purpose: This research examines the factors that influence organic food purchasing decisions of kindergartens in Ho Chi Minh City, Vietnam. Research Design, Data, and Methodology: A mixed-method research was utilized in this study. It included a focus group of 10 participants and a survey of 304 respondents, (quantitative research) who are employed in the selected kindergartens, using both online and paper surveys based on nonprobability and convenient sampling. The SPSS and SmartPLS 3 software were used to analyze data. Results: a) Eight factors affect the purchase decision of kindergartens; b) Environment Attention, Normative Beliefs, Trust belief on brand, Cost of meal set, and Reference group positively affect Intention behavior; c) Feeling safe positively affect Perceived Quality Product. Perceived quality of product and Intention behavior positively affect organic food Purchase Decision of kindergartens. Conclusion: Eight factors affect organic food purchasing decisions of kindergartens in Ho Chi Minh City. This study offers recommendation and solutions for a stable output of organic products in Vietnam, and ways to popularize them within the community.