• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2082-2102
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• 2018

In recent years, social network related applications such as WeChat, Facebook, Twitter and so on, have attracted hundreds of millions of people to share their experience, plan or organize, and attend social events with friends. In these operations, plenty of valuable information is accumulated, which makes an innovative approach to explore users' preference and overcome challenges in traditional recommender systems. Based on the study of the existing social network recommendation methods, we find there is an abundant information that can be incorporated into probability matrix factorization (PMF) model to handle challenges such as data sparsity in many recommender systems. Therefore, the research put forward a unified social network recommendation framework that combine tags, trust between users, ratings with PMF. The uniformed method is based on three existing recommendation models (SoRecUser, SoRecItem and SoRec), and the complexity analysis indicates that our approach has good effectiveness and can be applied to large-scale datasets. Furthermore, experimental results on publicly available Last.fm dataset show that our method outperforms the existing state-of-art social network recommendation approaches, measured by MAE and MRSE in different data sparse conditions.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.297-307
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• 2021

Although there are several studies on the impact of pesticides use, there is no consistent conclusion about such evidence on capturing the socioeconomic independence. The propose of this paper is to investigate the economy-wide impact of pesticide use in Thailand. The research data and methodology in this paper are depended on a social accounting matrix framework incorporating the pesticide-related illness as an additional sector, following Resosudarmo and Thorbecke (1998), to explain the impact of the pesticides on the related agricultural sector, food sector, and the social welfare of different households. Thus, the main characteristics of the Thai economy can be comprehensively described by providing information contained in this framework. In this respect, the several data sets are constructed to include the economic and social structure interdependencies, which are necessary to analyze the policy implications, especially industrial policy. The results were analyzed according to the general equilibrium theory and the Leontief multiplier matrix. It reveals that the food industry and the economy are significantly affected by the pesticides. One of the most interesting findings of this paper suggest that the food sector needs to determine its output to avoid bottleneck situations and create equality across the food production system.

• Communications for Statistical Applications and Methods
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• v.19 no.4
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• pp.547-558
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• 2012

Social network analysis is a graphical technique to search the relationships and characteristics of nodes (people, companies, and organizations) and an important node for positioning a visualized social network figure; however, it is difficult to characterize nodes in a social network figure. Therefore, their relationships and characteristics could be presented through an application of correspondence analysis to an affiliation matrix that is a type of similarity matrix between nodes. In this study, we provide the relationships and characteristics around authors and keywords in the JKSS(Journal of the Korean Statistical Society) of the Korean Statistical Society through the use of social network analysis and correspondence analysis.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.255-259
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• 2022

The new social reality emerging amid the global rise of communication links and integration processes acutely emphasizes the problems of communication in large and small social systems. The method of their communication becomes one of the keys to ensuring global security. It has become the mission of humanitarian education to prepare the younger generations for life in a changing world with no image of the future and increasing uncertainty. In psychological and pedagogical research, there is a growing scientific interest in the problems of interaction of the individual with the social environment. The mental trace of a person's practice in society shapes the experience of social interaction, which constitutes simultaneously the source, tool, and condition for the emergence and development of personality. The study outlines the methodological foundations for the study of individual experiences of social interaction. A hypothesis about the productivity of the functional matrix method is tested. Materials for the training of specialists in the humanities include interdisciplinary approaches to the study and transformation of the experience of social interaction and systematic methodology for the study of complex objects. Fundamental to the study is the systematic-dialectical method, and the matrix method is employed as the instrumental-technological method. The paper presents the results of a multidisciplinary overview of scientific literature concerning the essential characteristics and functions of social interaction and the respective experience. The overview points to the fragmented nature of scientific understanding of the elements of experience outside its integrity and systemic properties. Based on the formula "personality interacts with the social environment", the study presents an algorithm for the application of a systematic methodology for the study of complex objects, which made it possible to identify the system parameters of experience at three levels of cognition and develop the reference structural and functional matrices for the didactic system of its pedagogical enrichment.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.153-169
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• 2011

Today using Internet environment is considered absolutely essential for establishing corporate marketing strategy. Companies have promoted their products and services through various ways of on-line marketing activities such as providing gifts and points to customers in exchange for participating in events, which is based on customers' membership data. Since companies can use these membership data to enhance their marketing efforts through various data analysis, appropriate website membership management may play an important role in increasing the effectiveness of on-line marketing campaign. Despite the growing interests in proper membership management, however, there have been difficulties in identifying inappropriate members who can weaken on-line marketing effectiveness. In on-line environment, customers tend to not reveal themselves clearly compared to off-line market. Customers who have malicious intent are able to create duplicate IDs by using others' names illegally or faking login information during joining membership. Since the duplicate members are likely to intercept gifts and points that should be sent to appropriate customers who deserve them, this can result in ineffective marketing efforts. Considering that the number of website members and its related marketing costs are significantly increasing, it is necessary for companies to find efficient ways to screen and exclude unfavorable troublemakers who are duplicate members. With this motivation, this study proposes an approach for managing duplicate membership based on the social network analysis and verifies its effectiveness using membership data gathered from real websites. A social network is a social structure made up of actors called nodes, which are tied by one or more specific types of interdependency. Social networks represent the relationship between the nodes and show the direction and strength of the relationship. Various analytical techniques have been proposed based on the social relationships, such as centrality analysis, structural holes analysis, structural equivalents analysis, and so on. Component analysis, one of the social network analysis techniques, deals with the sub-networks that form meaningful information in the group connection. We propose a method for managing duplicate memberships using component analysis. The procedure is as follows. First step is to identify membership attributes that will be used for analyzing relationship patterns among memberships. Membership attributes include ID, telephone number, address, posting time, IP address, and so on. Second step is to compose social matrices based on the identified membership attributes and aggregate the values of each social matrix into a combined social matrix. The combined social matrix represents how strong pairs of nodes are connected together. When a pair of nodes is strongly connected, we expect that those nodes are likely to be duplicate memberships. The combined social matrix is transformed into a binary matrix with '0' or '1' of cell values using a relationship criterion that determines whether the membership is duplicate or not. Third step is to conduct a component analysis for the combined social matrix in order to identify component nodes and isolated nodes. Fourth, identify the number of real memberships and calculate the reliability of website membership based on the component analysis results. The proposed procedure was applied to three real websites operated by a pharmaceutical company. The empirical results showed that the proposed method was superior to the traditional database approach using simple address comparison. In conclusion, this study is expected to shed some light on how social network analysis can enhance a reliable on-line marketing performance by efficiently and effectively identifying duplicate memberships of websites.

• Korean Journal of Social Welfare Studies
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• v.40 no.1
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• pp.261-296
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• 2009

I constructed the 2003 Korean 'social accounting matrix'(SAM) to analyze the multipliers of total demand for each economic activity. I find that the relative magnitude of the influence of the welfare policy to the national economy measured by input-output production multipliers tends to be underestimated compared to SAM multipliers. This is because the total demand multipliers of SAM include the private sector effects, which is not considered in the input-output model. The result also support that income inflows in public service areas including education, health and social work, generate gains in the relative income of households.

• Genomics & Informatics
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• v.17 no.2
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• pp.18.1-18.10
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• 2019

Prediction of the relations among drug and other molecular or social entities is the main knowledge discovery pattern for the purpose of drug-related knowledge discovery. Computational approaches have combined the information from different sources and levels for drug-related knowledge discovery, which provides a sophisticated comprehension of the relationship among drugs, targets, diseases, and targeted genes, at the molecular level, or relationships among drugs, usage, side effect, safety, and user preference, at a social level. In this research, previous work from the BioNLP community and matrix or matrix decomposition was reviewed, compared, and concluded, and eventually, the BioNLP open-shared task was introduced as a promising case study representing this area.

• Journal of Korea Water Resources Association
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• v.47 no.2
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• pp.95-106
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• 2014

This paper analyses the economic effects of the water industry on the Korean economy by using Social Accounting Matrix (SAM). The SAM is constructed based on the Input-Output table, National account and Family income and expenditure survey for Korea in 2009. Through the SAM multiplier analysis, I estimate the effects of water investment. As the results, this study has found the followings. i) output multiplier effects of water sector are 5.300~7.741, ii) value added multiplier effects of water sector are 0.685~1.158, iii) income multiplier effects of water sector are 0.511~0.984, iv) redistributed income multiplier effects of water sector are -0.096~0.247. The results indicate that a significant influence on the industrial production and the household income in Korea.

• Proceedings of the Technology Innovation Conference
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• 1997.07a
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• pp.175-194
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• 1997

The competitive power of technologies is required for survival of enterprises in the social environments that change rapidly. So the strategy of technology development becomes more and more important. For the establishment of strategy, the situational analysis and the forecasting analysis are executed and they include the technology assessment and the technological forecasting. The technology assessment is systematical examination and analysis of the present status of technology. Among the various methods of technology assessment, Matrix Method is one of the usual methods. This research is intended to find out the problems and the difficulties in the current Matrix Method, and to improve the method, finally to help the R&D departments of enterprises applying the method. This suggested matrix(TSM Technology Shift Matrix) method is designed so that one can judge the current situation of technology and future expectation, by moving the matrix which is placed to the upside of the basic matrix.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.49
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• pp.143-152
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• 1999

The competitive advantage of technologies is required for survival of enterprises in the social environments which change rapidly. So the strategy of technology development becomes more and more important. For the establishment of strategy, the situational analysis and the forecasting analysis are executed and they include the technology assessment and the technology forecasting. This research is intended to find out the problems and the difficulties in the current Matrix Method, and to improve the method, finally to help the R&D departments of enterprises applying the method. The suggested matrix(TSM : Technology Shift Matrix) method is designed so that one can judge the current situation of technology and future trend, by moving the matrix which is placed to the upside of the basic matrix.