• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1270-1271
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• 2011

소셜 네트워크 서비스는 가트너에서 2011년에 이어 2012년에도 각광받을 기술의 하나로 선정된 만큼 미래 인터넷의 핵심 키워드 중 하나로도 뽑히며, 엔터테인먼트, 검색, 방송, 커머스 등의 여러 가지 서비스와 직접 연결된다. 이러한 소셜 네트워크 서비스 가운데 하이브리드형 서비스는 사용자의 정보를 관리 및 파악하여 사용자가 원하는 제품을 예측하고 추천해주고 있으며, 이를 위해 그래프 마이닝 기술을 적용하고 있다. 하지만 그래프 마이닝 기술은 아직 복잡한 그래프 구조의 데이터에서 정보를 추출하기에 제약사항들이 발생하므로 이에 대하여 많은 연구가 활발히 이루어지고 있다. 이러한 그래프 마이닝 기술을 나아가 더 발전시켜 활용하면 기존의 하이브리드형 서비스에서 사용자의 정보를 파악하여 충성도를 높여줄 뿐 아니라 기업에서의 타켓 마케팅과 원투원 마케팅을 가능하게 해주고 기존 사용자에 대한 교차 판매와 격상판매의 전략들을 도출할 수 있을 것이다.

• Journal of KIISE
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• v.41 no.12
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• pp.1117-1125
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• 2014

Folksonomy data, which is derived from social tagging systems, is a useful source for understanding a user's intention and interest. Using the folksonomy data, it is possible to create an accurate user profile which can be utilized to build a personalized search system. However there are limitations in some of the traditional methods such as Vector Space Model(VSM) for user profiling and similarity computation. This paper suggests a novel method with graph-based user and document profile which uses the proximity information of query terms to improve personalized search. We demonstrate the performance of the suggested method by comparing its performance with several state-of-the-art VSM based personalization models in two different folksonomy datasets. The results show that the proposed model constantly outperforms the other state-of-the-art personalization models. Furthermore, the parameter sensitivity results show that the proposed model is parameter-free in that it is not affected by the idiosyncratic nature of datasets.

• Journal of KIISE:Information Networking
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• v.36 no.2
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• pp.69-79
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• 2009

Today's Internet is one of the necessaries of our life. Anomalies of the Internet provoke social problems. For that reason, Internet Measurement which studies characteristics on Internet traffic attracts pubic attention. Recently, Traffic Dispersion Graph (TDG), a novel traffic analysis method, was proposed. The TDG is not a statistical analysis method but a graphical visualization method on interactions among network components. In this paper, we propose a new anomaly detection paradigm and its technique using TDG. The existing studies have focused on detecting anomalous packets of flows. On the other hand, we focus on detecting the sources of anomalous traffic. To realize our paradigm, we designed the TDG Clustering method. Through this method, we could classify anomalous hosts infected by various worm viruses. We obtained normal traffic through dropping traffic of the anomalous hosts. Especially, we expect that the TDG clustering method can be applied to real-time anomaly detection because calculations of the method are fast.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.403-415
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• 2017

In this paper, we investigate cosponsorship networks found in the 17th National Assembly of Republic of Korea. New legislation should be sponsored by at least 10 legislators including one main sponsor. Cosponsorship networks can be constructed, using directional links from cosponsors of legislation to its main sponsor; subsequently, these networks indicate the social relationships among the legislators. We apply Exponential Random Graph Model (ERGM) for valued networks to capture structural properties and the covariate effects of networks. We find the effect of the same party has the greatest influence on the composition of the network. Mutuality also plays an important role in the cosponsorship network; in addition, the effect of the number of elections won by a legislator has a small but significant influence.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.149-161
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• 2012

In the customer-centered world, which is used internet and social network services actively, it is important that their needs should be embraced into systems. Our study proposes a technique to normalize and select 1,800 customer's needs at C company. In order to normalize the requirements, we have specified requirements by considering a standard for requirements specification, have identified a set of keywords of requirements and have constructed a relation-graph of requirements. The graph presents objectives to design and build a system, and shows a degree of relative importance for each requirement. And then, we propose a techniques for requirements selection according to their contribution points, which are calculated using relative degree. We demonstrates our techniques by a case study of C company.

• Journal of the Korean Institute of Educational Facilities
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• v.24 no.4
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• pp.15-24
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• 2017

This paper aims to investigate in what extent subject-centered clusters are different from one another in terms of message system, which is composed of curriculum, pedagogy and evaluation. For this, Bernstein's pedagogic transmission code(i.e., classification and framing) and school typology(i.e., open-type or close-type) have been explored, and then applied into Shimin Junior School, Japan, in order to find out substantial characteristics between subject-centered clusters. In this case study, VGA(visibility graph analysis), as one of syntactical methodologies in space syntax theory, has been used to measure to what degree they are actually different. Throughout in-depth investigation of spatial configurations, it can be said that the square of clusters is strongly connected and integrated very well, so that it acts as an anchor place for school life within a cluster. However, it works in different ways according to message systems. In the subjects like Japanese and Science whose message system are characterized by strong classification and strong framing, integration values are relatively low, and this means that it is hard to expect cross-referencing activities through the subject squares. On the contrary, the subject of Social Studies defined by weak classification and weak framing shows the highest mean integration values, and this can be expected that there are inter-changeable learning activities in the square.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.527-541
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• 2022

A company is a social group of many individuals that work together to obtain better results, and it is an organization that pursues common goals such as profit. As a result, forming networks among members, as well as individual communication abilities, is critical. The purpose of this research was to determine what factors influence the creation of employee advice relationships. Using the ERGM(Exponential Random Graph Model) approach, we looked at the network data of 44 individuals from consulting firms with offices in the United States and Europe. The significance of structural network factors like connectivity was first discovered. Second, the gender factor had the most significant main influence on the likelihood of adopting each other's advice. Third, geographical homogeneity resulted in higher link probabilities than major impacts of gender. This research looked at ways to make a company's network more efficient and active.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3836-3854
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• 2022

The student group division is benefit for universities to do the student management based on the group profile. With the widespread use of student smart cards on campus, especially where students living in campus residence halls, students' daily activities on campus are recorded with information such as smart card swiping time and location. Therefore, it is feasible to depict the students with the daily activity data and accordingly group students based on objective measuring from their campus behavior with some regular student attributions collected in the management system. However, it is challenge in feature representation due to diverse forms of the student data. To effectively and comprehensively represent students' behaviors for further student group division, we proposed to adopt activity data from student smart cards and student attributes as input data with taking account of activity and attribution relationship types from different perspective. Specially, we propose a novel student group division method based on a multi-view student attribute heterogeneous information network (MSA-HIN). The network nodes in our proposed MSA-HIN represent students with their multi-dimensional attribute information. Meanwhile, the edges are constructed to characterize student different relationships, such as co-major, co-occurrence, and co-borrowing books. Based on the MSA-HIN, embedded representations of students are learned and a deep graph cluster algorithm is applied to divide students into groups. Comparative experiments have been done on a real-life campus dataset collected from a university. The experimental results demonstrate that our method can effectively reveal the variability of student attributes and relationships and accordingly achieves the best clustering results for group division.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.76-84
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• 2012

Visualizations have played an important role in understanding new insights of users of social network for social network analysis. Most of the previous works of visualization focus on representing user's relationship on social network by a complex multi dimension graph. However, this method is difficult to identify the important of relationship to focus on personal user intuitively. Besides, the user's messages to reflect the interrelation between users is insufficient, since most of visualization methods represent the user relationship using information of interaction between nodes on networks. In order to resolve above problem, this paper proposes a new visualization method to visualize user based hierarchy that uses internal relationship of users by fuzzy relational product and external access information of network.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.23 no.2
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• pp.174-185
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• 2010

Objective : In period of convalescence and aftereffect, facial palsy patients suffer from social and psychological problems, besides experiencing physical inconvenience. So Quality of life is important Evaluation in treatment or facial palsy. Nevertheless the aims of recent study were only trying to explain about objective symptoms. Therefore, Oriental-Western Medicine was performed, effectiveness of treatment were measured in Quality of life. Methods : Acute facial palsy patients who visiting whin 5days completed questionnaire about Quality of life, if he(or she) participated voluntarily. Questionnaire are comprised of general characteristics, Facial Disability Index(FDI), WHOQOL-BREF, VAS and House-Brackmann grade. Questionnaire used two times, the first medical examination and 4weeks later after starting Oriental-Western Medicine. The statistical analysis was performed by GraphPad Prism 4.0. T-test was used to verify effectiveness between the two groups. Results : 1. When we compared the first medical examination with 4weeks later, score of FDI-Physical function and FDI-Social/Well-bieng function increased but they were not valid statistically. 2. When we compared the first medical examination with 4weeks later, in WHOQOL-Brefoverall domain and physical domain, score increased. In WHOQOL-Bref-psychological, Social, Environment domain, score decreased. but, they were not valid statistically. 3. VAS, House-Brackmann grade decreased, but, they were not valid statistically. Conclusion : The number of subjects with facial palsy in our study(N=5) was too small, and the period of study(4 weeks) was short, too. For this reason, our data were not valid statistically. But Facial palsy Patient's Quality of life has risen.