• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.5
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• pp.385-393
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• 2013

In the past decade, a paradigm shift from machine-centered to human-centered and from technology-driven to user-driven has been witnessed. Consequently, Social search is getting more social and Social Network Service (SNS) is a popular Web service to connect and/or find friends, and the tendency of users interests often affects his/her who have similar interests. If we can track users' preferences in certain boundaries in terms of Web search and/or knowledge sharing, we can find more relevant information for users. In this paper, we propose a novel Topic Sensitive_Social Relationship Rank (TS_SRR) algorithm. We propose enhanced Web searching idea by finding similar and credible users in a Social Network incorporating social information in Web search. The Social Relation Rank between users are Social Relation Value, that is, for a different topics, a different subset of the above attributes is used to measure the Social Relation Rank. We observe that a user has a certain common interest with his/her credible friends in a Social Network, then focus on the problem of identifying users who have similar interests and high credibility, and sharing their search experiences. Thus, the proposed algorithm can make social search improve one step forward.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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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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• v.12 no.1
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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.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.317-326
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• 2018

The purpose of this study is to develop an AHP model to evaluate the relative importance and priorities of multi-cultural policies under bounded Rationality. The results of the study are as follows. First, in the evaluation elements for each measurement area, the following are the stable social settlement support policy (1rank), social capability development policy of multi-cultural family second generation (2rank), socio-economic activity policy (3rank), collaborative governance policy enforcement(4rank). Second, the priority of the measurement element is as follows. social settlement service target expansion policy was proved to be the top priority project stable social settlement support policy aspect and social capacity development policies of the second generation of multi-cultural families, social support policy was most important evaluated. Active economic activity support policy was as the top priority project socio-economic activity policy, and construct cooperation system of policy practice main agents was proved to be the top priority collaborative governance policy enforcement. These results will contribute to explain the reality of multi-cultural policy.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.71-77
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• 2015

This paper implements an estimated closeness centrality ranking algorithm in large-scale workflow-supported social networks and performance analyzes of the algorithm. Existing algorithm has a time complexity problem which is increasing performance time by network size. This problem also causes ranking process in large-scale workflow-supported social networks. To solve such problems, this paper conducts comparison analysis on the existing algorithm and estimated results by applying estimated-driven RankCCWSSN(Rank Closeness Centrality Workflow-supported Social Network). The RankCCWSSN algorithm proved its time-efficiency in a procedure about 50% decrease.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.2
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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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• v.9 no.1
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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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• v.56 no.4
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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.

• Journal of Information Technology Services
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• v.22 no.1
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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.

• Quality Improvement in Health Care
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• v.9 no.2
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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.