• 한국콘텐츠학회논문지
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• 제17권1호
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• pp.662-672
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• 2017

최근 모바일 기기와 근거리 무선 통신 기술 등의 발달로 기존 중앙 집중 처리 시스템의 한계를 개선하기 위해 모바일 P2P 네트워크에 대한 연구가 활발하게 진행되고 있다. 모바일 P2P네트워크에서 피어는 배터리, 메모리, 저장 공간 등과 같은 제한적인 요소들을 가진다. 모바일 P2P 네트워크에서 안전한 콘텐츠 공유를 위해서는 피어의 신뢰성이 판별되어야 한다. 본 논문에서는 제한된 모바일 P2P 네트워크에서 신뢰도를 판별하는 기법을 제안한다. 제안하는 기법은 피어의 평가 정보를 이용하여 직접적으로 피어가 평가한 값과 다른 피어가 평가한 간접적인 평가 값을 이용하여 피어의 신뢰성을 판별한다. 피어가 가지는 평가 정보로 최근 갱신 시간을 활용한다. 피어 평가 정보의 최근 갱신 시간을 비교하여 평가 정보 공유 시 중복되는 평가 정보를 감소시킨다. 성능 평가를 통해 제안된 기법이 메시지 수를 감소시키며 신뢰성에 대한 정확도를 향상 시키는 것을 입증한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권2호
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• pp.138-153
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• 2010

The interactions between people who do not know each other have been greatly increased with the on-going increase of people's cyberspace activities. In this situation, there exist potential risk factors such as the possibility of fraud, so we need a method to reduce or eliminate those risk factors. Concerning this necessity, rating systems are widely used, and many trust metrics calculated from rate values that people give to each other are proposed to help them make decisions. However, the trust metrics decrease the accuracy, and this is caused by the different rating scales and ranges of each person. So, we propose a fuzzy adjustment method to solve this problem. It is possible to catch the exact meaning of the trust value that each person selects through applying fuzzy sets, which improve the accuracy of the trust metric calculated from the trust values. We have applied our fuzzy adjustment method to the TidalTrust algorithm, a representative algorithm for calculating the local scalar trust metric, and we performed an experimental evaluation with four data sets and three evaluation methods.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2007년도 춘계학술대회
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• pp.190-196
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• 2007

With the rapid development of electronic commerce, online reputation management systems are of increasing importance in building trust and managing risk. Reputation rating mode and aggregating method are the most crucial parts of a reputation management system. In this paper, we analyze the merits and disadvantages associated with the rating mode and aggregating approach of current reputation management systems, and put forward some suggestions. These suggestions are helpful in improving current reputation management systems and developing new reputation management systems.

• 아태비즈니스연구
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• 제12권3호
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• pp.235-250
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• 2021

Purpose - This study analyzed the correlation and influence between social support, trust (seller, brand), and continuous purchase intention in C2C social commerce in China. Design/methodology/approach - To test the hypothesis, SPSS and Smart PLS 3.0 statistical packages were used based on the collected data. Findings - First, it was confirmed that social support (emotional support, informational support) had a positive effect on trust in sellers. Second, it was found that trust in sellers had a positive effect on brand trust. Third, both seller trust and brand trust have a positive effect on consumers' continuous purchase intention. Research implications or Originality - When consumers gain emotional and informational support from sellers, trust in sellers will be effectively improved. Companies wishing to improve brand credibility of their products will have to outsource the sale of their products to trusted sellers. The C2C social commerce platform should build its own trust rating system, recommend sellers with high reliability ratings, and encourage sellers to provide consumers with a lot of information about their brand.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.109-134
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• 2018

Collaborative Filtering (CF) is widely used in recommendation field, which can be divided into rating-based CF and learning-to-rank based CF. Although many methods have been proposed based on these two kinds of CF, there still be room for improvement. Firstly, the data sparsity problem still remains a big challenge for CF algorithms. Secondly, the malicious rating given by some illegal users may affect the recommendation accuracy. Existing CF algorithms seldom took both of the two observations into consideration. In this paper, we propose a recommendation method based on listwise learning-to-rank by incorporating users' social information. By taking both ratings and order of items into consideration, the Plackett-Luce model is presented to find more accurate similar users. In order to alleviate the data sparsity problem, the improved matrix factorization model by integrating the influence of similar users is proposed to predict the rating. On the basis of exploring the trust relationship between users according to their social information, a listwise learning-to-rank algorithm is proposed to learn an optimal ranking model, which can output the recommendation list more consistent with the user preference. Comprehensive experiments conducted on two public real-world datasets show that our approach not only achieves high recommendation accuracy in relatively short runtime, but also is able to reduce the impact of malicious ratings.

• Journal of Information Technology Applications and Management
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• 제24권1호
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• pp.169-185
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• 2017

This study proposes a novel recommendation algorithm that reflects the results from trust/distrust network analysis as a solution to enhance prediction accuracy of recommender systems. The recommendation algorithm of our study is based on memory-based collaborative filtering (CF), which is the most popular recommendation algorithm. But, unlike conventional CF, our proposed algorithm considers not only the correlation of the rating patterns between users, but also the results from trust/distrust relationship network analysis (e.g. who are the most trusted/distrusted users?, whom are the target user trust or distrust?) when calculating the similarity between users. To validate the performance of the proposed algorithm, we applied it to a real-world dataset that contained the trust/distrust relationships among users as well as their numeric ratings on movies. As a result, we found that the proposed algorithm outperformed the conventional CF with statistical significance. Also, we found that distrust relationship was more important than trust relationship in measuring similarities between users. This implies that we need to be more careful about negative relationship rather than positive one when tracking and managing social relationships among users.

• Journal of Contemporary Eastern Asia
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• 제20권1호
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• pp.102-119
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• 2021

Social credit rating in China (SCRC) has been criticized as "dystopian" and "Orwellian," an attempt by the Communist Party to hold onto power by exerting ever greater control over its citizens. To explain such measures, value differences are often invoked, that Chinese value stability and cooperation over privacy and freedom. However, these explanations are oversimplifications that result in ethical impasses. This article argues social credit rating should be understood in terms of the commonly human problem of large-scale cooperation. To do so, this paper relies on a cultural evolutionary framework and is an exercise in interpretive pros hen ethical pluralism, attempting to understand how apparently irresolvable cultural differences stem from common human concerns. Wholesale condemnation of SCRC fails to acknowledge the serious, intractable nature of problems resulting from a lack of trust in China. They take for granted the existence of institutions ensuring largescale, anonymous cooperation characteristic of - but somewhat unique to - Western Educated Industrialized Rich and Democratic (WEIRD) cultures. Because of its history and rapid development, China lacks the institutions necessary to ensure such cooperation, and because of anti-social punishment, social credit rating might be one of the few ways to ensure cooperation at this scale. The point is not to defend social credit rating in general, but to raise the possibility of its defense in China and show one way this would be done.

• The Journal of Asian Finance, Economics and Business
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• 제3권4호
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• pp.39-42
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• 2016

NFPs support a sustainable society and they rely on contributions from donors. Donor behavior is a kind of consumer behavior that influences fundraising by NFPs. In order to make fundraising functional under a principal-agent relationship, NFPs must construct trust through proper provision of accounting information. For donors, financial statements are main source of accounting information. Edelman revealed that the level of trust in Japan's NFPs is the lowest in East Asia, because of a lack of transparency and accountability. Some researchers had investigated donor behavior as a kind of consumer behavior and had provided supportive results that accounting information influences donor behaviors, before this research was conducted. This research investigates this background by conducting questionnaire-based survey. Main questions of this questionnaire were created according to criteria that BBB are using for NFPs in the U.S. The results of this survey revealed the lack of reliability of basic accounting information in Japan and that education in higher educational institutions can improve this situation. This survey also revealed that a rating agency like BBB, which evaluates accounting information of NFPs, could improve trust on NFPs. The implications of this study can apply to the other countries and regions where trust in NFPs is insufficient.

• 지능정보연구
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• 제23권2호
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• pp.19-38
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• 2017

본 연구는 사용자 평점 이외에 사용자 간 직접 간접적 신뢰 및 불신 관계 네트워크의 분석 결과를 추가로 반영한 새로운 하이브리드 협업필터링(Collaborative filtering, CF) 추천방법을 제안한다. 구체적으로 사용자 간의 유사도를 계산할 때 사용자 평가점수의 유사성만을 고려하는 기존의 CF와 다르게, 사용자 신뢰 및 불신 관계 데이터의 사회연결망분석 결과를 추가적으로 고려하여 보다 정교하게 사용자 간의 유사도를 산출하였다. 이 때, 사용자 간의 유사도를 재조정하는 접근법으로 특정 이웃 사용자가 신뢰 및 불신 관계 네트워크에서 높은 신뢰(또는 불신)를 받을 때, 추천 대상이 되는 사용자와 해당 이웃 간의 유사도를 확대(강화) 또는 축소(약화)하는 방안을 제안하고, 더 나아가 최적의 유사도 확대 또는 축소의 정도를 결정하기 위해 유전자 알고리즘(genetic algorithm, GA)을 적용하였다. 본 연구에서는 제안 알고리즘의 성능을 검증하기 위해, 특정 상품에 대한 사용자의 평가점수와 신뢰 및 불신 관계를 나타낸 실제 데이터에 추천 알고리즘을 적용하였으며 그 결과, 기존의 CF와 비교했을 때 통계적으로 유의한 수준의 예측 정확도 개선이 이루어짐을 확인할 수 있었다. 또한 신뢰 관계 정보보다는 불신 관계 정보를 반영했을 때 예측 정확도가 더 향상되는 것으로 나타났는데, 이는 사회적인 관계를 추적하고 관리하는 측면에서 사용자 간의 불신 관계에 대해 좀 더 주목해야 할 필요가 있음을 시사한다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2004년도 학술발표회
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• pp.1326-1330
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• 2004

This study analyzes the rubber-dam of hydrologic character to be located in a Nagdong-river main stream in Dasamyeon Juggogli of the Dae-gu global city lot the river environment monitoring. The purpose of this research investigates the influence according to the rubber-dam install scientificly. A result natural disposition, prepare the gauge to matte the width of the area of the understanding and the computation of the rating which Apply is possible. Into the result of this research, $Q=898.8h^2-26126h+189886$ edge was computed to the rating. Also this study use the now rate to get for an upside expression and analysis a water balance. Through the officer to be efficient a hereafter seminar zero and processing of the data to be acquired, the supplementation so that this study can share the data to the online. High practical use of the The self-governinig body of the data and data confirmed report which loses in the trust will be achieved.