• Title/Summary/Keyword: Design Recommendation System

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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.

Design of Music Recommendation System Considering Context-Information in the Home Network (홈 네트워크에서 상황정보를 고려한 음악 추천 시스템 설계)

  • Song Chang-Woo;Kim Jomg-Hun;Lee Jung-Hyun
    • Journal of KIISE:Computer Systems and Theory
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    • v.33 no.9
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    • pp.650-657
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    • 2006
  • The music is a part of our daily life in these days. And when the people listen to the music, they are affected by the context. However, previous researches on the music recommendation system have the problem that they didn't consider the proper contextual information efficiently. They only used the content-based filtering or the method to use musical metadata (genre, artist, etc.). Recently, there are some researches about the music recommendation system which applies the status(temperature, humidity, etc.) of environments. But, it is difficult to be accepted by the contextual information. Therefore, we propose the music recommendation system that is dynamically applied by the contextual information as well as the metadata in the previous researches. And the system can provide users with the music that they want to listen to, and then the users can be more satisfied. Also, the services can be improved by the feedback of the users. In order to solve this problem, the context-information for selecting a music list is defined and the music recommendation system is designed by using the content-based filtering method. The system is suitable for the user's taste and the context. The music recommendation system we are proposing uses an OSGi framework in the home network. As a result, the satisfaction of users and the quality of services will be improved more efficiently by supporting the mobility of services as well as the distributed processing.

Development of Hybrid Filtering Recommendation System using Context-Information in Mobile Environments (모바일 환경에서 상황정보를 이용한 하이브리드 필터링 추천시스템 설계)

  • Ko, Jung-Min;Nam, Doo-Hee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.10 no.3
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    • pp.95-100
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    • 2011
  • Due to rapid growth and development of telecommunication information technology, interest has been amplified regarding ubiquitous network computing and user-oriented service. Also, the rapid development of related technologies has been a big spotlight. Smart phone, with features such as a PC with advanced features is a mobile phone. According to environment and infrastructure development, a variety of mobile-based application software to provide various kinds of information and services has been released. However, most of them are provider-driven information systems and aim to provide large amounts of information simply to an unspecified number of users. Therefore, customized or personalized provision of information and service explained earlier for individual users has been hardly come true. According to background and need, this study wants to design and implement recommendations system for personalization and customization in mobile environments. To acquire more accurate recommendation results, recommendation system shall be composed using the Hybrid Filtering. Effective information recommendation according to user's situation by using user's context-information of purpose and location that are available in mobile devices before running the filtering of the information to improve the quality of recommendations.

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.

Personal Recommendation Service Design Through Big Data Analysis on Science Technology Information Service Platform (과학기술정보 서비스 플랫폼에서의 빅데이터 분석을 통한 개인화 추천서비스 설계)

  • Kim, Dou-Gyun
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.28 no.4
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    • pp.501-518
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    • 2017
  • Reducing the time it takes for researchers to acquire knowledge and introduce them into research activities can be regarded as an indispensable factor in improving the productivity of research. The purpose of this research is to cluster the information usage patterns of KOSEN users and to suggest optimization method of personalized recommendation service algorithm for grouped users. Based on user research activities and usage information, after identifying appropriate services and contents, we applied a Spark based big data analysis technology to derive a personal recommendation algorithm. Individual recommendation algorithms can save time to search for user information and can help to find appropriate information.

Design and Implementation of Personalized News Recommendation System Considering User Reading Habit under Smartphone Environment (스마트폰 환경에서 기사 읽기 습관 고려한 뉴스 추천 시스템 설계 및 구현)

  • Song, Teuk-Seob
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.7
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    • pp.1628-1633
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    • 2014
  • In this paper, we propose a news article recommendation system that reflects users' areas of interest and reading habits. Users can select interesting subject then our proposed system displays interesting articles above the other articles. Also the proposed system reflects users' dynamic interests using analyse of user's reading habits. The method of dynamic interest applies the different weight values from users simply clicking and reading entire articles. When users read articles from specific areas, the prosed system increases the weight of these specific areas using XML structure information. Hence users can read their articles of interest with ease.

A study on medical herb recommendation system using word2vec (word2vec을 이용한 한약재 추천 시스템 연구)

  • Ahn, Joo-Eon;Kim, Yeon-Ju;Kim, Hun-Sung;Kim, Woo-je;Lee, Yunho
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2017.01a
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    • pp.83-85
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    • 2017
  • 여러 약재의 복합적인 작용으로 치료를 행하는 한의학의 특성으로 여러 처방과 약재 조합들을 기억하고 있어야 하는 한의사의 어려움을 줄이고 환자에게 보다 높은 질의 의료 서비스를 제공할 수 있는 환경을 만드는 것이 목적이다. 다양하고 복합적인 약재의 조합으로 증상을 치료하는 한의학의 특성 때문에 셀 수 없이 많은 약재의 조합이 존재하며 한의사가 이 모든 조합을 기억하기는 어렵기 때문에 한의사들이 환자를 처방함에 있어 조금이라도 보탬이 될 수 있는 처방 지원 시스템을 개발할 필요가 있다. word2vec을 이용하여 처방과 약재의 조합을 추천해주며 분석을 통해 산출된 약재의 조합과 그 조합이 실제 의서에 존재하는지의 여부를 함께 알려주어 한의사가 보다 더 주의하여 환자에게 처방할 수 있다.

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A Study on Design and Implementation of Personalized Information Recommendation System based on Apriori Algorithm (Apriori 알고리즘 기반의 개인화 정보 추천시스템 설계 및 구현에 관한 연구)

  • Kim, Yong
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.23 no.4
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    • pp.283-308
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    • 2012
  • With explosive growth of information by recent advancements in information technology and the Internet, users need a method to acquire appropriate information. To solve this problem, an information retrieval and filtering system was developed as an important tool for users. Also, users and service providers are growing more and more interested in personalized information recommendation. This study designed and implemented personalized information recommendation system based on AR as a method to provide positive information service for information users as a method to provide positive information service. To achieve the goal, the proposed method overcomes the weaknesses of existing systems, by providing a personalized recommendation method for contents that works in a large-scaled data and user environment. This study based on the proposed method to extract rules from log files showing users' behavior provides an effective framework to extract Association Rule.

Effects of Independent Operator's Company Selection Attributes on Economic and Non-Economic Satisfaction, Trust, and Recommendation in the Network Marketing Industry (네트워크 마케팅 산업에서 독립 사업자의 기업 선택 속성이 경제적 및 비경제적 만족과 신뢰, 추천의도에 미치는 영향)

  • Roh, Hyun-Sik
    • The Korean Journal of Franchise Management
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    • v.10 no.1
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    • pp.19-32
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    • 2019
  • Purpose - Since the opening of Korea's distribution market, the domestic network marketing market has been continuing to grow. In this context, research on network marketing independent operators, which plays the most important role in the network marketing industry, is insufficient. This study was to identify the effects of Independent Operator's Company Selection Attributions on the Economic and Non-Economic Satisfaction, Trust, and Recommendation. The results will provide strategic direction, theoretical and practical implications for companies and operators in the network marketing industry. Research design, data, and methodology - In order to verify the research hypotheses, the data were collected from Independent Operators of Network marketing industry using questionnaires. The pretest was conducted from January 8 to 19, 2018, and the main survey was conducted from February 1 to 28. A total of 210 questionnaires, of which 193 copies were collected. The data were analyzed with SPSS 21.0. and AMOS 21.0. Results - The results are as follows; product competitiveness and system competitiveness have significant effects on economic satisfaction and non-economic satisfaction. Economic and non-economic satisfaction have significant effects on business trust. Economic and non-economic satisfaction did not influence recommendation intention directly, but influence it indirectly. Business trust has a significant effect on business recommendation intention. Conclusions - After starting network marketing business as an independent operator, the competitiveness of the company is meaningless, and product competitiveness and system competitiveness are important factors for economic and non-economic satisfaction. Therefore, network marketing companies and independent operators should prioritize product competitiveness and system competitiveness between business development. The findings show that trust in the business is very important for active business Recommendation to others. Therefore, network marketing firms and independent operators need to make efforts to meet economic and non-economic satisfaction, which have a significant impact on business trust.

Study on User Experience of Personalized Recommendation Systems of Fashion Vertical Platforms -The Regulation Effect of Self-Regulatory Focus- (패션 버티컬 플랫폼 개인화 추천시스템의 사용자 경험에 관한 연구 -자기조절초점의 조절효과-)

  • Min-Ji Park;Hyun-Hee Park;Yang-Suk Ku
    • Journal of the Korean Society of Clothing and Textiles
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    • v.47 no.4
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    • pp.711-728
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    • 2023
  • This study aims to validate the user experience associated with the personalized recommendation systems of fashion vertical platforms. The investigation focused on women aged 18 to 30 with prior experience using personalized fashion recommendation systems. The collected data were analyzed using SPSS 26.0 and AMOS 26.0, and the outcomes can be summarized as follows. Firstly, the diversity and usefulness of information quality exerted a positive effect on use satisfaction. Secondly, the affirmative impact of the reliability of system quality on user satisfaction was established, although stability was not confirmed. Thirdly, the study identified a favorable connection between ease-of-use of service quality and user satisfaction, while the influence of tangibles was unsubstantiated. Fourthly, the degree of self-reference was found to have a positive effect on user satisfaction. Fifthly, a constructive relationship emerged between user satisfaction and both continuous-use intention and recommendation intention. Lastly, there was a significant difference in the magnitude of the effect of ease-of-use on satisfaction according to self-regulatory focus. The findings of this study hold the potential to enhance the explanatory and predictive power of the field of consumer behavior within the novel shopping landscape of fashion vertical platforms.