• 제목/요약/키워드: Group Recommendation

검색결과 401건 처리시간 0.031초

Organic Water Additive on Growth Performances, Hematological Parameters and Cost Effectiveness in Broiler Production

  • Saha, Munmun;Chowdhury, Sachidananda Das;Hossain, Md. Elias;Islam, Md. Kamrul;Roy, Bishwajit
    • Journal of Animal Science and Technology
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    • 제53권6호
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    • pp.517-523
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    • 2011
  • The experiment was conducted with 144 broiler chicks from day-old to 5 weeks of age to investigate the efficacy of a water additive in broiler production. The chicks were randomly distributed into four different treatments namely T1 (control), T2 (water additive as per recommendation level), T3 (25% less than recommendation) and T4 (25% more than recommendation). Body weight of control group was higher in 2nd week of age, but at the end of the experiment additive groups showed higher values compare to control (p<0.05). Body weight gain was increased and feed conversion ratio was improved in the additives groups during the finishing and total period, although feed intake was different among the additive groups (p<0.05). When the hematological parameters were evaluated, packed cell volume and total erythrocytes counts were increased in the additive group that received 25% more than recommendation, and hemoglobin in 25% less than recommendation group. Mean cell volume and mean cell hemoglobin of the additive groups showed lower (p<0.05) values compare to the control, but other parameters were not affected. Sales price and profit were significantly higher in the additive groups compare to the control, although total production cost was increased in the additive groups (p<0.05). All levels of water additive increased profit in comparison with the control but 25% less than recommendation level appeared to be most profitable and cost effective. It also suggests that any additive considered for poultry, must undergo trial for determining efficacy as well as its cost effectiveness for application.

독거가구 및 기초생활수급 여부와 절주권고, 음주문제 상담 간의 연관성 분석 (the Association between the Single-Person Household & Beneficiary of National Basic Livelihood and Recommendation to Refrain Drinking Alcohol, Counseling for Drinking Problems)

  • 양정민;김하은;김재현
    • 한국병원경영학회지
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    • 제27권4호
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    • pp.13-21
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    • 2022
  • Purpose: The purpose of this study was to analyze the association between single-person households & Beneficiary of National Basic Livelihood and recommendation on alcohol consumption, and counseling on drinking problems for adults 19 years of age or older. Methods: In this study, excluding missing values, the association between the single-person household & Beneficiary of National Basic Livelihood and recommendation to refrain drinking alcohol, counseling for drinking problems was analyzed by using the chi-squre test and logistic regression analysis. Results: In the case of non-single person households, compared to single-person households, the recommendation rate to refrain drinking alcohol was 1.519 OR (Odds Ratio [OR]: 1.159 , p-value <.0001). meanwhile, in the case of Beneficiary of National Basic Livelihood, the recommendation rate to refrain alcohol consumption was higher by 1.414 OR (OR: 1.414, p-value: 0.011), and the drinking problem counseling rate was also higher by 2.257 OR (OR: 2.257, p-value: 0.026) compared to non-beneficiary group. Discussion & Conclusion: Based on the 2016-2019 National Health and Nutrition Survey, this study investigated the associaiton between single households & Beneficiary of National Basic Livelihood and recommendations to refrain alcohol, and counseling on drinking problems. Compared to the Beneficiary of National Basic Livelihood group, single-person household group has recently been classified as a socially vulnerable group, but it is not applicable in the policy category. If policy and institutional measures for treatment are provided, it is expected that the problem of alcohol abuse can be reduced.

소셜 네트워크 기반 맞춤형 콘텐츠 추천 시스템 (Personalized Contents Recommendation System Based on Social Network)

  • 이석필
    • 방송공학회논문지
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    • 제18권1호
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    • pp.98-105
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    • 2013
  • 최근의 미디어 생성/소비 패턴은 UCC 같은 소비자가 직접 미디어를 생성하고 소비하는 프로세스가 등장하여 일반화되고 있다. 그동안 다양한 콘텐츠 중에서 사용자가 원하는 콘텐츠만을 제공하기 위해 사용자 프로파일을 이용한 콘텐츠 추천 엔진에 대한 연구가 많이 진행되어왔다. 본 연구는 사용자 프로파일 이외에 다종의 멀티미디어 콘텐츠의 소비를 바탕으로 사용자들을 소셜 네트워킹화하고 이를 통해 유사 콘텐츠 선호패턴을 가진 구성원들의 사용자 프로파일을 바탕으로 개인화된 맞춤형 콘텐츠를 추천할 수 있는 추천 에이전트를 개발하였다. 개발한 추천 에이전트는 방송/통신망 상에 존재하는 다양한 콘텐츠 중에 사용자의 선호패턴과 일치하는 콘텐츠들을 추천하고 소셜 네트워크상의 사용자들간의 연관성을 통해 선호도를 갱신하는 시스템이다.

사용자 피드백 정보 기반의 학습된 생활 스포츠 팀 추천 서비스 시스템 설계 및 구현 (A Study on the Design and Implementation of the Learned Life Sports Team Recommendation Service System based on User Feedback Information)

  • 이현호;이원진
    • 한국멀티미디어학회논문지
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    • 제21권2호
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    • pp.242-249
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    • 2018
  • In this paper, the customized sports convergence contents curation system is proposed for activation of life sports. The proposed system collects and analyzes profile of social sports group (club, society, etc.) for recommending optimized sports convergence contents to user. In addition, the feedback based on the recommendation result from the user is continuously reflected and the optimal recommendation is made possible. For the system evaluation, the proposed system is tested to 300 users (about 20 sports team) for about 3 months and the system is verified by analyzing the initial recommendation results and recommendation results reflected by user feedback.

When Do Consumers Get More Delighted? : Role of Surprise and Attribute Importance

  • Lee, Eun-Young
    • 유통과학연구
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    • 제16권8호
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    • pp.5-13
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    • 2018
  • Purpose - Customer Delight is an important issue for firms and academia since delighted consumers reveal higher repurchase intentions than merely satisfied consumers and become loyal consumers. This research investigates customer delight, especially focusing on the role of surprise and attribute importance via experiment. Research design, data, and methodology - An experiment consisting of experiment, reference, and control group was performed with virtual online bookstore. For the analysis, one-way ANOVA and post-hoc analysis (LSD) were performed. Results - The experiment group that was delighted with surprise revealed the highest repurchase intention and recommendation intention among the other groups (H1 supported). Then each group was divided into attribute importance high and attribute importance low. For the group that was delighted in important attribute revealed higher repurchase and recommendation intention than the group that was delight in less important attribute (H2 supported). Conclusions - This research contributes academically for investigating the research area of customer delight and focusing on the role of surprise and attribute importance. For practical implications, this research provides information about customer delight and its several moderating variables that it is important to delight customers with surprising experience and focusing on an important attribute that consumers perceive not on a less important attribute.

소비자의 감성과 소비유형을 이용한 협업여과기반 콘텐츠 추천 기법 (A Contents Recommendation Scheme Based on Collaborative Filtering Using Consumer's Affection and Consumption Type)

  • 최인복;박태근;이재동
    • 정보처리학회논문지D
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    • 제15D권3호
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    • pp.421-428
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    • 2008
  • 협업여과 기법은 추천 시스템에서 널리 사용되는 기술이지만, 소비자의 참조그룹을 선정하는 방법에 따라 추천의 정확도가 달라지는 특성을 가지고 있다. 이에 본 논문에서는 콘텐츠 추천의 정확도를 높이기 위하여 소비자의 감성과 소비유형을 참조그룹으로 하여 협업여과기반으로 콘텐츠를 추천하는 기법을 제안한다. 소비자의 감성을 기쁨, 슬픔, 혐오, 행복, 이완 다섯 가지로 구분하고, 소비유형을 저실용/저쾌락, 저실용/고쾌락, 고실용/저쾌락, 고실용/고쾌락 네 가지로 구분하여 콘텐츠 추천 기법의 성능을 분석한 결과, 본 논문에서 제안하는 기법으로 콘텐츠를 추천한 경우가 소비자 감성과 소비유형을 고려하지 않은 전체 참조그룹으로 추천한 경우보다 정확도가 향상됨을 확인하였다.

Digital Signage System Based on Intelligent Recommendation Model in Edge Environment: The Case of Unmanned Store

  • Lee, Kihoon;Moon, Nammee
    • Journal of Information Processing Systems
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    • 제17권3호
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    • pp.599-614
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    • 2021
  • This paper proposes a digital signage system based on an intelligent recommendation model. The proposed system consists of a server and an edge. The server manages the data, learns the advertisement recommendation model, and uses the trained advertisement recommendation model to determine the advertisements to be promoted in real time. The advertisement recommendation model provides predictions for various products and probabilities. The purchase index between the product and weather data was extracted and reflected using correlation analysis to improve the accuracy of predicting the probability of purchasing a product. First, the user information and product information are input to a deep neural network as a vector through an embedding process. With this information, the product candidate group generation model reduces the product candidates that can be purchased by a certain user. The advertisement recommendation model uses a wide and deep recommendation model to derive the recommendation list by predicting the probability of purchase for the selected products. Finally, the most suitable advertisements are selected using the predicted probability of purchase for all the users within the advertisement range. The proposed system does not communicate with the server. Therefore, it determines the advertisements using a model trained at the edge. It can also be applied to digital signage that requires immediate response from several users.

다단계 알고리즘을 이용한 개인화 상품추천 (Personalized Commodity Recommendation Using A Multi-Stage Algorithm)

  • 장병철;최덕원;이동철
    • 정보처리학회논문지D
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    • 제10D권7호
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    • pp.1225-1230
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    • 2003
  • 많은 사이버 쇼핑몰들은 다양한 추천 방법을 도입하여 상품을 추천하고 있다. 상세한 알고리즘은 공개되어 있지 않지만 대부분 비교적 단순한 알고리즘을 쓰고 있다. 본 연구는 상품 자체의 특성, 소비자 집단의 특성, 그리고 소비자 개인의 특성을 고려한 다단계 알고리즘을 이용하여 상품추천 능력을 향상시키고자 시도하였다. 소비자와 관련된 더 많은 요인을 고려함에 따라 상품추천의 내용이 변화하는 사례를 도표로 비교 예시하였다.

Movie Recommendation Algorithm Using Social Network Analysis to Alleviate Cold-Start Problem

  • Xinchang, Khamphaphone;Vilakone, Phonexay;Park, Doo-Soon
    • Journal of Information Processing Systems
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    • 제15권3호
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    • pp.616-631
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    • 2019
  • With the rapid increase of information on the World Wide Web, finding useful information on the internet has become a major problem. The recommendation system helps users make decisions in complex data areas where the amount of data available is large. There are many methods that have been proposed in the recommender system. Collaborative filtering is a popular method widely used in the recommendation system. However, collaborative filtering methods still have some problems, namely cold-start problem. In this paper, we propose a movie recommendation system by using social network analysis and collaborative filtering to solve this problem associated with collaborative filtering methods. We applied personal propensity of users such as age, gender, and occupation to make relationship matrix between users, and the relationship matrix is applied to cluster user by using community detection based on edge betweenness centrality. Then the recommended system will suggest movies which were previously interested by users in the group to new users. We show shown that the proposed method is a very efficient method using mean absolute error.

대표성 기반 뉴스 추천 메커니즘이 온라인 뉴스 포탈의 독자 반응에 미치는 영향 (The Effect of Representativeness in News Recommendation Mechanisms on Audience Reactions in Online News Portals)

  • 이은곤
    • 한국전자거래학회지
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    • 제21권2호
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    • pp.1-22
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    • 2016
  • 최근 온라인 뉴스 포탈의 뉴스 추천 메커니즘이 뉴스 콘텐츠를 수집, 선택, 편집 및 왜곡하는 일이 일어나고 있다. 선행연구들은 뉴스의 가치에 대한 일관된 정의를 내리지도, 뉴스의 가치가 독자의 반응에 어떤 영향을 미치는지 실증적으로 검증하지도 못했다. 본 연구는 선행연구의 뉴스 가치 개념을 종합하고, 뉴스 가치를 아우를 수 있는 개념으로 대표성의 개념을 도입하였으며, 대표성 기반 정보발견법 및 정보 수용 모델을 활용하여, 대표성이 인지된 뉴스 품질, 신뢰, 인지된 유용성, 서비스 만족도, 충성도, 지속사용의도, 구전의도 등 독자 반응에 어떠한 영향을 미치는 지를 실증적으로 검증하였다. 시나리오 설문 법을 통해 총 357개의 유효한 자료가 수집되었다. 각 집단들은 1) 시간 순서기반 뉴스 추천 메커니즘, 2) 조회수 기반 뉴스 추천 메커니즘, 3) 편집자에 의해 선택된 주요 뉴스를 다시 조회수 기반으로 정렬한 뉴스 추천 메커니즘의 세 종류의 메커니즘에 각각 노출되었다. MANOVA 분석결과에 따르면, 편집자에 의해 선택된 주요 뉴스를 다시 조회수 기반으로 정렬한 뉴스 추천 메커니즘만이 여타 집단에 비해 인지된 뉴스 품질과 신뢰에서 유의한 차이를 보였다. PLS 분석 결과에 따르면, 이렇게 형성된 인지된 뉴스 품질과 신뢰는 인지된 유용성, 서비스 만족도, 충성도, 지속사용의도, 구전의도 등 독자 반응을 유의하게 증가시키는 것으로 조사되었다. 본 연구의 학술적 기여는 언론 영역에서 정보기술의 역할을 강조하고, 편집자와 독자 모두가 인정하는 뉴스가 가치 있는 뉴스라고 개념화 하였으며, 뉴스 추천 메커니즘의 효과를 실증한 가치를 가진다. 실무적 측면에서 본 연구는 온라인 뉴스 포탈이 편집자와 독자의 시각이 모두 반영된 절충안의 뉴스 추천 메커니즘을 활용하는 것이 독자를 유인하기 위해 도움이 될 것이라고 제안한다.