• Journal of Information Processing Systems
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• v.19 no.2
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• pp.189-202
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• 2023

In the era marked by information inundation, social network analysis is the most important part of big data analysis, with clique detection being a key technology in social network mining. Also, detecting maximal balance clique in signed networks with positive and negative relationships is essential. In this paper, we present two algorithms. The first one is an algorithm, MCDA1, that detects the maximal balance clique using the improved three-way concept lattice algorithm and object-induced three-way concept lattice (OE-concept). The second one is an improved formal concept analysis algorithm, MCDA2, that improves the efficiency of memory. Additionally, we tested the execution time of our proposed method with four real-world datasets.

• Electronics and Telecommunications Trends
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• v.8 no.4
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• pp.177-185
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• 1993

본 고에서는 기존의 maximal cliques 탐색 알고리즘들을 조사하여 분석하고 문제점들을 제시하여 상호 비교 분석함으로써 maximal cliques를 탐색하는 분야에 대한 알고리즘의 체계를 파악하고 기여할 수 있도록 노력하였다. 특히 기존의 clique 탐색 알고리즘들을 그들이 사용하는 기법에 따라서 point sequence method, line addition and removal technique, backtracking technique, 그리고 stack operation technique로 분류하고 각 기법에 해당하는 사례 알고리즘들을 분석하여 장단점들을 파악하며 상호 비교 분석하는데 그 초점을 맞추었다.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1273-1284
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• 2016

In this paper, we analyzed the patents on machine learning using keyword network analysis and clique analysis. To construct a keyword network, important keywords were extracted based on the TF-IDF weight and their association, and network structure analysis and clique analysis was performed. Density and clustering coefficient of the patent keyword network are low, which shows that patent keywords on machine learning are weakly connected with each other. It is because the important patents on machine learning are mainly registered in the application system of machine learning rather thant machine learning techniques. Also, our results of clique analysis showed that the keywords found by cliques in 2005 patents are the subjects such as newsmaker verification, product forecasting, virus detection, biomarkers, and workflow management, while those in 2015 patents contain the subjects such as digital imaging, payment card, calling system, mammogram system, price prediction, etc. The clique analysis can be used not only for identifying specialized subjects, but also for search keywords in patent search systems.

• Korean Journal of Health Education and Promotion
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• v.22 no.2
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• pp.173-193
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• 2005

Objectives: The purpose of this study is to analyze the peer group factor related to adolescent smoking in the social structure(network) of adolescent groups, by applying the theory of social network. Methods: The data was collected from boy students of one high school located in Gun-Po city of Kyonggi Province. The total number of the sample was 605(223 first grade, 198 second grade, 184 third grade). The survey using the questionnaire was carried out in April 2005. Social position is finally classified as clique member, liaison, isolate group by using the NetMiner II 2.5 version. Results: The current smoking rate was 15.0%, and the life-time smoking rate was 34.9%. The smoking rate increased significantly, as the grade went up. And it was significantly high among the group having smoking friends. The logistic regression analysis showed that the odds ratio of the smoking friends group was about 4 times higher than the no smoking friends group in experience of smoking. But the smoking rate was higher significantly in the isolate group within the network composed of 2. person's social-link. The odds ratio of the isolate group was about 4.5 times higher than the clique member. However, this pattern was not found in the network composed of 3 person's social-link. Therefore, the hypothesis that clique member would have a correlation with smoking was rejected. In reality, the isolate group had a tendency of smoking more frequently. Conclusions: The result of this study suggests that the role of the peer group in smoking is to be considered in the prevention program. More attentions should be paid for the isolate group.

• ETRI Journal
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• v.37 no.5
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• pp.888-897
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• 2015

Group scheduling is an operation whereby control packets arriving in a time slot schedule their bursts simultaneously. Normally, those bursts that are of the same wavelength are scheduled on the same channel. In cases where the support of full wavelength converters is available, such scheduling can be performed on multiple channels for those bursts that are of an arbitrary wavelength. This paper presents a new algorithm for group scheduling on multiple channels. In our approach, to reach a near-optimal schedule, a maximum-weight clique needs to be determined; thus, we propose an additional algorithm for this purpose. Analysis and simulation results indicate that an optimal schedule is almost attainable, while the complexity of computation and that of implementation are reduced.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.5
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• pp.90-102
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• 2022

In recent years, as interest in healing increases, outdoor spaces with the concept of healing have been created. For more professional and in-depth planning and design, the perception and characteristics of outdoor healing places through social media posts were analyzed using NER. Text mining was conducted using 88,155 blog posts, and frequency analysis and clique cohesion analysis were conducted. Six elements were derived through a literature review, and two elements were added to analyze the perception and the characteristics of healing places. As a result, visitors considered place elements, date and time, social elements, and activity elements more important than personnel, psychological elements, plants and color, and form and shape when visiting healing places. The analysis allowed the derivation of perceptions and characteristics of healing places through keywords. From the results of the Clique, keywords, such as places, date and time, and relationship, were clustered, so it was possible to know where, when, what time, and with whom people were visiting places for healing. Through the study, the perception and characteristics of healing places were derived by analyzing large-scale data written by visitors. It was confirmed that specific elements could be used in planning and marketing.

• International Journal of Knowledge Content Development & Technology
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• v.8 no.2
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• pp.23-36
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• 2018

Institutional repositories (IR) are promising to be extremely advantageous to scholars especially in developing countries. IR initiatives started in India during the late nineties and the popularity of this concept is growing rapidly in the higher educational and research institutions to disseminate newly emerging knowledge and expertise. The purpose of this paper is to critically analyze the network links of IR websites among four IITs that are registered in open DOAR (Directory of Open Access Repositories) web portal. The Institutional Repositories chosen for the study are IIT Delhi, IIT Hyderabad, IIT Bombay, and IIT Kanpur. The analysis of the study focused on standard graph and network cohesion metrics, such as density, diameter, eccentricity and distances, and clustering coefficient; for an even more detailed analysis advanced centrality measures and fast algorithms such as clique census are used.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.403-410
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• 2021

Given an undirected simple graph, k-club is one of the proposed structures to model social groups that exist in various types in Social Network Analysis (SNA). Maximum k-Club Problem (MkCP) is to find a k-club of maximum cardinality in a graph. This paper introduces a Genetic Algorithm called HGA+DROP which can be used to approximate maximum k-club in graphs. Our algorithm modifies the existing k-CLIQUE & DROP algorithm and utilizes Heuristic Genetic Algorithms (HGA) to obtain multiple k-clubs. We experiment on DIMACS graphs for k = 2, 3, 4 and 5 to compare the performance of the proposed algorithm with existing algorithms.

• Journal of Information Technology Services
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• v.14 no.3
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• pp.49-65
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• 2015

As South Korean large business groups, also known as Chaebol, have broadened their influence in the domestic economy, it is important to analyze the influence of internal transactions among Chaebol affiliates on their performance. In this paper, relationship between internal transactions and efficiency of Chaebol affiliates has been analyzed. Top five Chaebol groups in South Korea are selected; they include Samsung, Hyundai Motors, LG, SK, and Lotte group. Based on internal transactions among affiliates, social networks are constructed for each Chaebol group to analyze centrality, network structures and cliques. Data Envelopment Analysis (DEA) was conducted to examine the efficiency of the Chaebol affiliates. Then, correlations between the degree centrality and the efficiency of Chaebol affiliates were analyzed, and the network structures of Chaebol groups are presented. The result shows that positive correlations between degree centrality and efficiency are observed among four Chaebol Groups. This paper shows that the Social Network Analysis (SNA) techniques can be used in the empirical research for the analysis of internal transactions of Chaebol groups.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.49.3-49
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• 2001

In 1994 Adelman´s pioneer work demonstrated that deoxyribonucleic acid (DNA) could be used as a medium for computation to solve mathematical problems. He described the use of DNA based computational approach to solve the Hamiltonian Path Problem (HPP). Since then a number of combinatorial problems have been analyzed by DNA computation approaches including, for example: Maximum Independent Set (MIS), Maximal Clique and Satisfaction (SAT) Problems. In the present paper we propose a method of solving another classic combinatorial optimization problem - the eraph Coloring Problem (GCP), using specifically designed circular DNA plasmids as a computation tool. The task of the analysis is to color the graph so that no two nodes ...