• Title/Summary/Keyword: Department Recommendation

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A Study on Story propose model based on Machine Learning - Focused on YouTube

  • CHUN, Sanghun;SHIN, Seung-Jung
    • International Journal of Internet, Broadcasting and Communication
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    • v.13 no.2
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    • pp.224-230
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    • 2021
  • YouTube is an OTT service that leads the home economy, which has emerged from the 2020 Corona Pandemic. With the growth of OTT-based individual media, creators are required to establish attractive storytelling strategies that can be preferred by viewers and elected for YouTube recommendation algorithms. In this study, we conducted a study on modeling that proposes a content storyline for creators. As the ability for Creators to create content that viewers prefer, we have presented the data literacy ability to find patterns in complex and massive data. We also studied the importance of compelling storytelling configurations that viewers prefer and can be selected for YouTube recommendation algorithms. This study is of great significance in that it deviated from the viewer-oriented recommendation system method and proposed a story suggestion model for individual creaters. As a result of incorporating this story proposal model into the production of the YouTube channel Tiger Love video, it showed a certain effectiveness. This story suggestion model is a machine learning text-based story suggestion system, excluding the application of photography or video.

Evaluations of Museum Recommender System Based on Different Visitor Trip Times

  • Sanpechuda, Taweesak;Kovavisaruch, La-or
    • Journal of information and communication convergence engineering
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    • v.20 no.2
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    • pp.131-136
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    • 2022
  • The recommendation system applied in museums has been widely adopted owing to its advanced technology. However, it is unclear which recommendation is suitable for indoor museum guidance. This study evaluated a recommender system based on social-filtering and statistical methods applied to actual museum databases. We evaluated both methods using two different datasets. Statistical methods use collective data, whereas social methods use individual data. The results showed that both methods could provide significantly better results than random methods. However, we found that the trip time length and the dataset's sizes affect the performance of both methods. The social-filtering method provides better performance for long trip periods and includes more complex calculations, whereas the statistical method provides better performance for short trip periods. The critical points are defined to indicate the trip time for which the performances of both methods are equal.

Effect of Market-Wholesaler System on Market Expansion, Re-transaction Intention, and Recommendation Intention

  • ROH, Gye-Ho;YI, Jong-Hyun;CHO, Young-Sam
    • Journal of Distribution Science
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    • v.18 no.5
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    • pp.99-109
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    • 2020
  • Purpose: This study aims to develop and empirically analyze a research model in order to comprehend the relationship among the service quality of market-wholesaler system, re-transaction intention, and recommendation intention of forwarder. Further, we suggest new six factors reflecting the service quality of market-wholesaler system and highlight market expansion of forwarder as a mechanism in the relationship. Research design, data and methodology: The authors developed the new scales measuring the service quality of market-wholesaler system (i.e. trade price, price fluctuation, payment receipt, settlement period, trade information, and customer service) and conducted a cross-sectional survey for 439 forwarders in a wholesale market. And then we performed a series of path analyses to test hypotheses. The hypotheses are as follows. [H1] The service quality of market-wholesaler system will positively affect forwarders' market expansion, [H2] Forwarders' market expansion will positively affect their re-transaction intention, [H3] Forwarders' market expansion will positively affect their recommendation intention, [H4] Forwarders' re-transaction intention will positively affect their recommendation intention. Results: The results showed that all the six factors for the service quality of market-wholesaler system were positively related to market expansion of forwarders. There was a differential effectiveness in the six factors of the service quality. More specifically, the positive effect of customer service factor was the strongest on market expansion of forwarders. And the respective effects of trade price, price fluctuation, settlement period, trade information factors were followed in order. The positive effect of payment receipt factor was the weakest on market expansion of forwarders. Also, market expansion of forwarders was positively related to their re-transaction intention and recommendation intention. Furthermore, market expansion of forwarders was indirectly related to recommendation intention through re-transaction intention as well. Conclusions: The research findings provide important theoretical and practical implications. This study is the first to attempt to test the perception of forwarders for the service quality of market-wholesaler system by developing and using the new scales. Also, there has been a sharp controversy about the effectiveness of market-wholesaler system. The findings support that market-wholesaler system would be activated by empirically verifying the effectiveness of the service quality on the various outcomes.

Factors Affecting International Patient's Satisfaction with Korea Medical Services, Revisit and Recommendation Intention (외국인 환자의 의료서비스 만족도, 재방문 의사, 추천 의사에 영향을 미치는 요인)

  • Kim, Myo-Gyeong;Choi, Yun-Kyoung;Ahn, Jung-Won;Kim, Keum Soon
    • Health Policy and Management
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    • v.27 no.1
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    • pp.63-74
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    • 2017
  • Background: This study aims to analyze quality of and satisfaction with Korea medical services and identify factors affecting medical service satisfaction, revisit, and recommendation intention among international patients. Methods: Secondary analysis of survey data conducted by Korea Health Industry Development Institute from June 10th to July 17th in 2013 was done using multiple regression and logistic regression analysis. The 191 international patients from 9 medical institutions in Seoul were enrolled. Results: The results showed that international patients were satisfied with 85.6 points out of 100.0 points. International patients appraised higher in staff service rather than other services. Factors influencing medical service satisfaction were gender, religion, medical specialty, length of stay, and quality of medical services. Quality of medical service explained 29.8% of medical service satisfaction and especially, 'doctor's care' and 'communication and patient respect' were significantly related to medical service satisfaction. Medical specialty had a significant influence on revisit intention. There were no statistically significant influencing factors of recommendation intention. Additionally, more satisfied patients were associated with higher revisit and recommendation intention. Conclusion: This study implies that quality of medical services is a critical factor for patient satisfaction and that satisfaction with medical services is an important factor for increasing revisit and recommendation intention among international patients. In addition, health care providers should consider cultural differences to enhance satisfaction with medical services for international patients. Therefore, multidimensional strategy is required to strengthen the cultural competency of healthcare providers.

The Effects of Banking Service Quality on Consumer Satisfaction andPositive Word-of- Mouth: With Special Comparisons according to Genderand Age Groups (은행서비스 질이 소비자만족도 및 긍정적 구전에 미치는 영향 : 성별, 연령집단에 따른 비교)

  • Jeong, Woon-Young;Kim, Young-Seen
    • Journal of the Korean Home Economics Association
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    • v.47 no.1
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    • pp.13-24
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    • 2009
  • The purpose of this study was to examine the effects of banking service quality on consumer satisfaction and positive word-of-mouth. A total of 330 bank consumers were investigated between Sept. 11 and Oct. 11, 2006. After sorting through the data, the responses of 299 consumer ( > 24 yrs old) were used for analysis. SERVPERF, the performance component of the Service Quality scale (SERVQUAL), was used to measure the four dimensions of reliability, responsiveness/empathy, assurance, and tangibles. Responses were partitioned by age and gender. The major findings were as follows; The effect of service quality by SERVPERF on consumer satisfaction and positive word-of-mouth did not differ according to gender. However, positive recommendation in males was directy related to the technical quality evaluate. In females, higher the functional quality evaluate was directly related to higher positive word-of-mouth recommendation. The effect of service quality by SERVPERF on consumer satisfaction was not revealed differently according to age. However, with respect to respondents under the age of 45, tangibles and assurance had a positive relationship with word-of-mouth recommendation. Furthermore, the higher the functional quality evaluate, the higher the level of positive word-of-mouth. Responsiveness/empathy was the most significant factor on positive word-of-mouth recommendation in respondents over the age of 45. In this age group, the higher the technical quality evaluate, the higher the level of positive word-of-mouth recommendation. These results have implications for banking service managers, particularly in improving service quality to increase consumer satisfaction and positive word-of-mouth. Future research is needed to replicate this study using more broad and representative samples in order to test the generalization of these findings.

Design a Method Enhancing Recommendation Accuracy Using Trust Cluster from Large and Complex Information (대규모 복잡 정보에서 신뢰 클러스터를 이용한 추천 정확도 향상기법 설계)

  • Noh, Giseop;Oh, Hayoung;Lee, Jaehoon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.1
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    • pp.17-25
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    • 2018
  • Recently, with the development of ICT technology and the rapid spread of smart devices, a huge amount of information is being generated. The recommendation system has helped the informant to judge the information from the information overload, and it has become a solution for the information provider to increase the profit of the company and the publicity effect of the company. Recommendation systems can be implemented in various approaches, but social information is presented as a way to improve performance. However, no research has been done to utilize trust cluster information among users in the recommendation system. In this paper, we propose a method to improve the performance of the recommendation system by using the influence between the intra-cluster objects and the information between the trustor-trustee in the cluster generated in the online review. Experiments using the proposed method and real data have confirmed that the prediction accuracy is improved than the existing methods.

Blockchain Technology for Mobile Applications Recommendation Systems (모바일앱 추천시스템과 블록체인 기술)

  • Umekwudo, Jane O.;Shim, Junho
    • The Journal of Society for e-Business Studies
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    • v.24 no.3
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    • pp.129-142
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    • 2019
  • The interest in the blockchain technology has been increasing since its inception and it has been applied to many fields and sectors. The blockchain technology creates a decentralized environment where no third party controls the data and transaction. Mobile apps recommendation has been extensively used to recommend apps to mobile users. For example, Android-based recommendation applications have been developed to recommend other mobile apps for download depending on user's preferences and mobile context. These recommendations help users discover apps by referring to the experiences of other users. Due to the collection of a large amount of data and user information, there is a problem of insecurity and user's privacy that are prone to be attacked. To address this issue the blockchain technology can be incorporated to assure cryptographic safety. In this paper, we present a survey of the on-going mobile app recommendations and e-commerce technology trend to address how the blockchain can be incorporated into the collaborative filtering recommendation systems to enable the users to set up a secured data, which implies the importance of user privacy preference on personalized app recommendations.

A Recommendation Model based on Character-level Deep Convolution Neural Network (문자 수준 딥 컨볼루션 신경망 기반 추천 모델)

  • Ji, JiaQi;Chung, Yeongjee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.3
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    • pp.237-246
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    • 2019
  • In order to improve the accuracy of the rating prediction of the recommendation model, not only user-item rating data are used but also consider auxiliary information of item such as comments, tags, or descriptions. The traditional approaches use a word-level model of the bag-of-words for the auxiliary information. This model, however, cannot utilize the auxiliary information effectively, which leads to shallow understanding of auxiliary information. Convolution neural network (CNN) can capture and extract feature vector from auxiliary information effectively. Thus, this paper proposes character-level deep-Convolution Neural Network based matrix factorization (Char-DCNN-MF) that integrates deep CNN into matrix factorization for a novel recommendation model. Char-DCNN-MF can deeper understand auxiliary information and further enhance recommendation performance. Experiments are performed on three different real data sets, and the results show that Char-DCNN-MF performs significantly better than other comparative models.

The Design of a Multiplexer for Multiview Image Processing

  • Kim, Do-Kyun;Lee, Yong-Joo;Koo, Gun-Seo;Lee, Yong-Surk
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.682-685
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    • 2002
  • In this paper, we defined necessary operations and functional blocks of a multiplexer for 3-D video systems and present our multiplexer design. We adopted the ITU-T's recommendation(H.222.0) to define the operations and functions of the multiplexer and explained the data structures and details of the design for multiview image processing. The data structure of TS(Transport Stream) and PES (Packetized Elementary Stream) in ITU-T Recommendation H.222.0 does not fit our multiview image processing system, because this recommendation is fur wide scope of transmission of non-telephone signals. Therefore, we modified these TS and PES stream structures. The TS is modified to DSS(3D System Stream) and PES is modified to SPDU(DSS Program Data Unit). We constructed the multiplexer through these modified DSS and SPDU. The number of multiview image channels is nine, and the image class employed is MPEG-2 SD(Standard Definition) level which requires a bandwidth of 2∼6 Mbps. The required clock speed should be faster than 54(= 6 ${\times}$ 9)㎒ which is the outer interface clock speed. The inside part of the multiplexer requires a clock speed of only 1/8 of 54㎒, since the inside part of the multiplexer operates by the unit of byte. we used ALTERA Quartus II and the FPGA verification for the simulation.

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Relationship Between Perceived Risk and Physician Recommendation and Repeat Mammography in the Female Population in Tehran, Iran

  • Moshki, Mahdi;Taymoori, Parvaneh;Khodamoradi, Sahmireh;Roshani, Daem
    • Asian Pacific Journal of Cancer Prevention
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    • v.17 no.sup3
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    • pp.161-166
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    • 2016
  • Iranian women are at high risk of low compliance with repeat mammography due to a lack of awareness about breast cancer, negative previous experiences, cultural beliefs, and no regular visits to a physician. Thus research is needed to explore factors associated with repeated mammography participation. Applying the concept of perceived risk as the guiding model, this study aimed to test the fit and strength of the relationship between perceived risk and physician recommendation in explaining repeat mammography. A total of 601 women, aged 50 years and older referred to mammography centers in region 6, were recruited via a convenience sampling method. Using path analysis, family history of breast cancer and other types of cancer were modeled as antecedent perceived risk, and physician recommendation and knowledge were modeled as an antecedent of the number of mammography visits. The model explained 49% of the variance in repeat mammography. The two factors of physician recommendation and breast self-examination had significant direct effects (P < 0.05) on repeat mammography. Perceived risk, knowledge, and family history of breast cancer had significant indirect effects on repeat mammography through physician recommendation. The results of this study provide a background for further research and interventions not only on Iranian women but also on similar cultural groups and immigrants who have been neglected to date in the mammography literature.