• Journal of Animal Science and Technology
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• v.53 no.6
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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.

• Korea Journal of Hospital Management
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• v.27 no.4
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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.

• Journal of Broadcast Engineering
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• v.18 no.1
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• pp.98-105
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• 2013

Patterns for generating and consuming contents are various in these days from conventional broadcasting contents to UCC. There are many researches on developing recommendation engines based on user's profile for providing desired contents. In this paper we propose a contents recommendation system using not only user's profile but other's profiles in closed user group of the social network based on patterns for user's consuming contents. The proposed recommendation agent update user's profile using usage history and other's profiles related to the user in the closed user group.

• Journal of Korea Multimedia Society
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• v.21 no.2
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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.

• Journal of Distribution Science
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• v.16 no.8
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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.

• The KIPS Transactions:PartD
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• v.15D no.3
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• pp.421-428
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• 2008

Collaborative filtering is a popular technique used for the recommendation system, but its performance, especially the accuracy of recommendation, depends on how to define the reference group. This paper proposes a new contents recommendation scheme based on collaborative filtering technique whose reference groups are created by consumer's affection and consumption type in order to improve the accuracy of recommendation. In this paper, joy, sadness, anger, happiness, and relax are considered as the consumer's affection. And, low-utility / low-pleasure, low-utility / high-pleasure, high-utility / low-pleasure, and high-utility / high-pleasure are considered as the consumer's shopping types. Experimental results show that the proposed scheme improves the accuracy of recommendation compared to the recommendation scheme considering neither consumer's affection nor consumption type.

• Journal of Information Processing Systems
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• v.17 no.3
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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.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1225-1230
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• 2003

Many cyber-shopping malls use various commodity recommendation methods. Although the detailed algorithms are not disclosed to the public, they mostly rely on relatively simple and straightforward methods. This paper intends to improve the commodity recommendation by using a multi-stage algorithm which considers factors that are characteristics of the commodity itself, of the consumer group, and of the individual customer. A comparison table is provided which shows whether there is a change in commodity recommendation as we consider more factors about the customer.

• Journal of Information Processing Systems
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• v.15 no.3
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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.

• The Journal of Society for e-Business Studies
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• v.21 no.2
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• pp.1-22
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• 2016

News contents has been collected, selected, edited and sometimes distorted by the news recommendation mechanisms of online portals in nowadays. Prior studies had not confirmed the consensus of newsworthiness, and they had not tried to empirically validate the impacts of newsworthiness on audience reactions. This study challenged to summarize the concepts of newsworthiness and validate the impact of representativeness of both editor's and audience's perspective on audience reactions as perceived news quality, trust on news portal, perceived usefulness, service satisfaction, loyalty, continuous usage intention, and word-of-mouth intention by adopting the representativeness heuristics method and information adoption model. 357 valid data had been collected using a scenario survey method. Subjects in each groups are exposed by 3 news recommendation mechanisms: 1) the time-priority news exposure mechanism (control group), 2) the reference-score-based news recommendation mechanism (a single treatment group), and 3) the major-news-priority exposure mechanism sorting by the reference scores made by peer audiences (the mixed treatment group). Data had been analyzed by the MANOVA and PLS method. MANOVA results indicate that only mixed method of both editor and audience recommendation mechanisms impacts on perceived news quality and trust. PLS results indicate that perceived news quality and trust could significantly affect on the perceived usefulness, service satisfaction, loyalty, continuance usage, and word-of-mouth intention. This study would contributions to empathize the role of information technology in media industry, to conceptualize the news value in the balanced views of both editors and audiences, and to empirically validate the benefits of news recommendation mechanisms in academy. For practice, the results of this study suggest that online news portals would be better to make mixed news recommendation mechanisms to attract audiences.