• 한국통신학회논문지
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• 제38B권5호
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• pp.385-393
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• 2013

지난 10여 년간, 정보기술 분야의 패러다임은 기계중심에서 인간중심으로, 기술기반에서 사용자가 쉽게 정보시스템에 참여하고 활용 할 수 있는 사용자 기반으로 변화되었다. 즉 소셜 네트워크를 이용하여 정보를 상호 공유하는 소셜 검색의 형태로 변화하고 있으며, 이와 같이 사람과 사람을 연결 해 주는 소셜 네트워크 서비스는 웹서비스와 융합을 통해 친구 맺기, 친구 찾기, 유사한 관심사를 갖고 있는 사람들과의 정보공유, 선호도 검색, 정보 추천시스템 등 다양한 분야에 활용되고 있다. 본 논문에서는 토픽 기반 소셜 관계 랭크(TS_SRR : Topic Sensitive_Social Relation Rank) 알고리즘을 제안한다. 제안 알고리즘은 소셜 네트워크 서비스를 웹 검색 엔진과 통합하는 것을 목적으로 하며, 소셜 관계 지수, 즉 Social Relation Rank와 검색 결과에 대한 선호도 사이의 상관관계를 분석하였다. 실험 과정에서 소셜 네트워크 안에 존재하는 일반적인 사람들은 정보 공유시 특정 분야에 대해 관심사가 유사할 경우 잘 모르는 타인들에 비해 친밀도가 높은 친구를 더 신뢰한다는 것을 확인 할 수 있었다. 따라서 제안 알고리즘은 소셜 검색의 신뢰성을 향상 시킬 수 있을 것으로 판단된다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2009년도 춘계학술발표대회
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• pp.364-368
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• 2009

"소셜 네트워크(Social Network)와 검색(Search)의 만남"은 현재 인터넷 상에서 매우 의미 있는 두 영역의 결합이다. 이와 같은 두 영역의 결합을 통해 소셜 네트워크 내에서 친구들의 생각이나 관심사 및 활동을 검색하고 공유함으로써 검색의 효율성과 적합성을 높이기 위한 연구들이 활발히 수행되고 있다. 본 논문에서는 일반적인 소셜 관계 랭크(SRR : Social Relation Rank) 및 토픽이 반영된 소셜 관계 랭크(TS_SRR : Topic Sensitive_Social Relation Rank) 알고리즘을 제안한다. SRR은 소셜 네트워크 내에 존재하는 웹 사용자들의 내재적인 특성 및 검색 성향 등에 대한 관련성(또는 유사정도)을 수치로 산정한 '소셜 관계 지수(SRV : Social Relation Value)'에 랭킹(Ranking)을 부여한 것을 의미한다. 제안하는 알고리즘의 검색 적용 가능성을 검증하기 위해 첫째, 웹 사용자간 직접 또는 간접적인 연결로 구성된 소셜네트워크를 구성 한다. 둘째, 웹 사용자들의 속성에 내재된 정보를 이용하여 토픽별 SRV를 산정한 후 랭킹을 부여하고, 토픽별 변화되는 랭킹에 따라 소셜 네트워크를 재구성 한다. 마지막으로 (TS_)SRR과 웹 사용자들의 검색 패턴(Search Pattern)을 비교 실험 한다. 실험 결과 (TS_)SRR이 높은 웹 사용자 간에는 검색 패턴 또한 유사함을 확인 하였다. 결론적으로 (TS_)SRR 알고리즘을 기반으로 관심분야에 연관성이 높은, 즉 상위에 랭크 된 웹 사용자들을 검색하여 검색 패턴을 공유 또는 상속받는 다면 개인화 검색(Personalized Search) 및 소셜 검색(Social Search)의 효율성과 신뢰성 향상에 기여 할 수 있다.

• 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.

• 한국콘텐츠학회논문지
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• 제18권11호
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• pp.317-326
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• 2018

본 연구는 제한된 합리성 하에서 다문화정책의 상대적 중요도와 우선순위를 도출하기 위해 AHP모델을 작성하여 전문가 평가를 실시하였다. 연구결과는 다음과 같다. 첫째, 측정영역에서는 안정된 사회정착지원정책(1순위), 다문화 가족 2세들의 사회적 역량개발 정책(2순위), 사회 경제활동 지원정책(3순위), 협력적 거버넌스(4순위)의 순으로 정책 우선순위가 평가되었다. 둘째, 측정요소의 우선순위이다. 안정된 사회정착 지원정책에서는 사회정착 서비스 대상 확대정책, 다문화 가족 2세들의 사회적 역량개발 정책에서는 사회적 진출지원 정책이 가장 중요하게 평가되었다. 사회 경제활동지원 정책에서는 적극적 경제활동 지원정책, 협력적 거버넌스 정책 추진에서는 정책실천주체들의 협력시스템 구축이 가장 중요한 정책 우선순위로 평가되었다. 이런 연구결과는 다문화정책을 현실적 차원에서 설명하는데 기여할 것으로 판단된다.

• 인터넷정보학회논문지
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• 제16권3호
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• pp.71-77
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• 2015

본 논문에서는 대규모 워크플로우 기반 소셜 네트워크를 위한 추정 근접 중심도 랭킹 알고리즘을 구현하고, 그에 대한 성능 분석을 수행한다. 기존의 근접 중심도 분석 방법은 특정 노드와 다른 모든 노드들 간의 최단거리를 구하므로 네트워크의 크기가 커짐에 따라 근접 중심도 분석 시간이 기하급수적으로 증가하는 문제점을 가진다. 이로 인해 대규모 소셜 네트워크의 근접 중심도 랭킹 과정에도 계산시간 문제를 가진다. 이러한 문제점을 개선하고자 본 논문에서는 추정기법을 활용한 근접 중심도 랭킹 알고리즘을 구현하며 기존 알고리즘과의 성능 분석을 수행한다. 이는 약 50%의 계산 시간 단축 결과를 보여주었다.

• Asian Pacific Journal of Cancer Prevention
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• 제15권2호
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• pp.623-627
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• 2014

Background: Esophagus cancer (EC) is among the five most common cancers in both sexes in Iran, with an incidence rate well above world average. Social rank (SR) of individuals and regions are well-known independent predictors of EC incidence. The aim of current study was to assess gender and social disparities in EC incidence across Iran's provinces through 2003-2009. Materials and Methods: Data on distribution of population at province level were obtained from the Statistical Centre of Iran. Age-standardized incidence rates of EC were gathered from the National Cancer Registry. The Human Development Index (HDI) was used to assess the province social rank. Rate ratios and Kunst and Mackenbach relative indices of inequality ($RII_{KM}$) were used to assess gender and social inequalities, respectively. Annual percentage change (APC) was calculated using joinpoint regression. Results: EC incidence rate increased 4.6% and 6.5% per year among females and males, respectively. There were no gender disparities in EC incidence over the study period. There were substantial social disparities in favor of better-off provinces in Iran. These social disparities were generally the same between males and females and were stable over the study period. Conclusions: The results showed an inverse association between the provinces' social rank and EC incidence rate in Iran. In addition, I found that, in contrast with international trends, women are at the same risk of EC as men in Iran. Further investigations are needed to explain these disparities in EC incidence across the provinces.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권1호
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• pp.421-433
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• 2015

Recently, there have been fast-growing social network services based on the Internet environment and web technology development, the prevalence of smartphones, etc. Social networks also allow the users to convey the information and news so that they have a great influence on the public opinion formed by social interaction among users as well as the spread of information. On the other hand, these social networks also serve as perfect environments for rampant malware. Malware is rapidly being spread because relationships are formed on trust among the users. In this paper, an effective patch strategy is proposed to deal with malicious worms based on social networks. A graph is formed to analyze the structure of a social network, and subgroups are formed in the graph for the distributed patch strategy. The weighted directions and activities between the nodes are taken into account to select reliable key nodes from the generated subgroups, and the Incremental PageRanking algorithm reflecting dynamic social network features (addition/deletion of users and links) is used for deriving the high influential key nodes. With the patch based on the derived key nodes, the proposed method can prevent worms from spreading over social networks.

• Journal of Preventive Medicine and Public Health
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• 제56권4호
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• pp.327-337
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• 2023

Objectives: Considering the importance of social determinants of health (SDHs) in promoting the health of residents of informal settlements and their diversity, abundance, and breadth, this study aimed to identify, measure, and rank SDHs for health promotion interventions targeting informal settlement residents in a metropolitan area in Iran. Methods: Using a hybrid method, this study was conducted in 3 phases from 2019 to 2020. SDHs were identified by reviewing studies and using the Delphi method. To examine the SDHs among informal settlement residents, a cross-sectional analysis was conducted using researcher-made questionnaires. Multilayer perceptron analysis using an artificial neural network was used to rank the SDHs by priority. Results: Of the 96 determinants identified in the first phase of the study, 43 were examined, and 15 were identified as high-priority SDHs for use in health-promotion interventions for informal settlement residents in the study area. They included individual health literacy, nutrition, occupational factors, housing-related factors, and access to public resources. Conclusions: Since identifying and addressing SDHs could improve health justice and mitigate the poor health status of settlement residents, ranking these determinants by priority using artificial intelligence will enable policymakers to improve the health of settlement residents through interventions targeting the most important SDHs.

• 한국IT서비스학회지
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• 제22권1호
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• pp.57-74
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• 2023

It has been pointed out as a limitation that the rank of some efficient DMUs(decision making units) cannot be discriminated due to the relativity nature of efficiency measured by DEA(data envelopment analysis), comparing the production structure. Recently, to solve this problem, a DEA-SNA(social network analysis) model that combines SNA techniques with data envelopment analysis has been studied intensively. Several models have been proposed using techniques such as eigenvector centrality, pagerank centrality, and hypertext induced topic selection(HITS) algorithm, but DMUs that cannot be ranked still remain. Moreover, in the process of extracting latent information within the DMU group to build effective network, a problem that violates the basic assumptions of the DEA also arises. This study is meaningful in finding the cause of the limitations by comparing and analyzing the characteristics of the DEA-SNA model proposed so far, and based on this, suggesting the direction and possibility to develop more advanced model. Through the results of this study, it will be enable to further expand the field of research related to DEA.

• 한국의료질향상학회지
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• 제9권2호
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• pp.134-147
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• 2002

Background : As an empirical study, current research about the quality of social services carried out in general and teaching hospitals across the country. In the flux of health care reforms and market transformation, the quality of social services in the hospital becomes increasingly significant. Methods : A sample of total 80 hospitals, including general hospitals with one social worker at least and single-department hospital with two social workers or more, were identified nationwide through the registry of Korean Association of Medical Social Workers and Korean Association of Hospitals. The subjects of this survey were 80 leaders of social service units. The survey data from each subjects were measured to evaluate level of quality that service provider perceived of sample hospitals. Under the method of one-way ANOVA and multiple regression, the level of quality in social work service was analyzed. Results : The major findings were as following ; First, the level of quality perceived showed less score, especially the lowest was the score of quality of outcome. Second, the key variables of each hospital which turned out significantly different in quality of social work service were the departmental form of social work unit, unit leader's age, educational level, field experience, and job rank. Third, the level of quality of social work service correlated positively with the field experience of unit leader, the size of social work unit, the job rank of the unit leader. Conclusion : The most influential variables to the quality of social work service proved departmental form of social work unit, leader of social work unit. Therefore, to assure the proper level of quality, social work unit in hospital must be structured single, independent department in which entitled social worker is supposed to supervise and manage. And a leadership-development program for leaders in social work unit are strongly recommended.