• Information Systems Review
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• v.12 no.1
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• pp.1-22
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• 2010

Demands onenterprise applications are changing drastically in terms of service and value. Currently enterprises have started to view these applications as service systems, as they combine technology with organizational networks designed to deliver services that satisfy the needs of customers and marketing operations. Social networking is playing a crucial role in this direction and provides organizations with the critical data that enable to build strong relationships with their customers and partners. Enterprises have started using this concept, by integrating social networking services with their enterprise applications such as CRM. In this paper, we combine an open source social networking engine with a CRM (Customer Relationship Management) application to constitute a social CRM system. This can bring the customers closer to the enterprise and facilitate better communication with them. Social Networking Analysis constructs were used to analyze the effectiveness of service system. In the current competitive and economically challenging conditions, salespeople needs to quickly and effectively establish meaningful communication with customers. Our approach can address this issue, by handling the changing customer demands in minimal time, and increases service quality and business value.

• Journal of Science and Technology Studies
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• v.18 no.3
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• pp.255-289
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• 2018

The social problem-solving R&D is different from the goal and process in comparison with research aimed at scientific excellence and industrial innovation. It pursues social values and active participation of the end-user civil society. In this study, we try to derive its characteristics by analyzing the cases that are evaluated as successful social problem solving R&D project. In order to analyse the social problem-solving R & D case, these four variables are selected; 1) social and technological planning for problem solving 2) participatory technological development 3) law, system and delivery system development for innovation deployment 4) scale-up of new R&D process. Those are important issues identified through case studies: 1) the tools and support services needed to carry out social and technical planning effectively, 2) the role of the Living Lab to coordinate opinions with experts and users, 3) the legislative and institutional improvement activities as important as technological development, 4) researcher's change through interaction with end user.

• Journal of Korea Port Economic Association
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• v.37 no.1
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• pp.121-142
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• 2021

The purpose of this study is to identify environmental factors affecting manpower utilization of container terminals. 300 questionnaires were distributed to employees working in terminal operators in Busan and Gwangyang port. Based on the results of multiple regression analysis, first, it is proved that technology development, organizational culture and social·external environment have a significant impact on manpower utilization of container terminals. Second, this study found that technology development and social·external environment have a significant impact on manpower utilization of container terminals system. Third, it is found that technology development, social·external environment, safety and security change the composition of the workforce between office and field employees. Forth, the number of workforce is expected to gradually decrease due to technology development. Finally, it is found that technology development, organizational culture, social·external environment and terminal operation have a impact on specialization and training system of human resoures.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.3-3
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• 2017

The question of how to establish sustainable agricultural systems has become as prominent as questions related to water, energy and climate change. High input/high output agriculture has brought with it many adverse effects; the massive deterioration of soil and water in both quantity and quality, increased greenhouse gas emissions and an increased prevalence of unsafe foods. Additionally, urbanization and climate change has worsened the shortage of farmland and reduced the supply of agricultural water. Given these challenges, maintaining, conserving and efficiently using agri-environmental resources, through fostering of sustainable agriculture, have emerged as key tasks in solving these problems. What is needed therefore is research, based on systematic and comprehensive empirical analyses, that can propose plans and methods for establishing an appropriate sustainable agricultural system. The empirical analysis of sustainable agricultural system is approached separately from economic, environmental and social aspects. An analysis of environment effect reveals that the available phosphate level is 1.3~2.1 times greater than the optimal amount in rice paddies, upland fields and orchards. Further examination has revealed that the excess nutrient is polluting both ground water and surface water. Analytical results for economic feasibility show that factors of production have been invested heavily in the rice crop. Under these conditions, sustainable agriculture, including low-input agriculture, appears to be a possible alternative that will facilitate simultaneous improvements in both economic feasibility and environment effects. Analysis results for sociality reveal that social factors include the value of producer, association and interior networks. Social conditions are comprised of leadership, consumers' awareness, education and conflict solutions. In addition, analysis as to the degree investments contribute to improving agricultural value added has revealed that the direct payment program is the most effective instrument. Experts confirm that economic feasibility can be improved by scientific and well-reasoned nutrient management on the basis of soil testing. Farmers pointed to 'economic factors' as being the largest obstacle to switching to the practice of sustainable agriculture. They also indicate 'uncertainty with regards to sustainable agriculture technology' as an impediment to practicing sustainable agriculture. Even so, farmers who believe environmental and regional issues to be the most pressing problems have expanded their practice of sustainable agriculture. The keys to establishing sustainable agriculture system are classified into the following four aspects. Firstly, from an economic aspect, the research indicates that agricultural policy needs to be integrated with environmental policy and that the function of market making based on the value chain needs to be revitalized. Secondly, from an environmental aspect, there is a need for an optimal resource management system to be established in the agricultural sector. In addition, sustainable agriculture practice will need to be extended with attendant environmentally-friendly and sustainable intensive technology also requiring further development. Thirdly, from a social aspect, green agriculture management needs to be fostered, technology and education extended, and social conflict mediated. Lastly, from a governance aspect, it will be necessary to strengthen good governance, assign and share suitable roles and responsibilities, build a cooperation system and utilize community supported agriculture.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.388-397
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• 2012

Recently, one of the received attraction fields in web based service is 'Human Relationship Service' that is called SNS. This relationship map service is able to deliver information to user more easily and visually because it is intuitive data that is linked with offline real world. While past map service put physical real information in the map, present map service is evolving into new communicative platform that expresses social relationship beyond simple search platform that shows real world. In this paper, we propose smart social grid system using sketch map that is based on online map service structure. This system has features such as standardized interface provision for various SNS, use to governance hub tool in case of establishing a personal network through expanded social grid, a role of bridge to mashup software linked with other SNS, user environment construction that reproduces social grid data, and the faster service setup by improved search technology.

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1245-1255
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• 2010

In current Web 2.0 environment, one of the most core technology is social bookmarking which users put tags and bookmarks to their interesting Web pages. The main purpose of social bookmarking is an effective information service by use of retrieval, grouping and share based on user's bookmark information and tagging result of their interesting Web pages. But, current social bookmarking system uses the number of bookmarks and tag information separately in information retrieval, where the number of bookmarks stand for user's degree of interest on Web contents, information retrieval, and classification serve the purpose of tag information. Because of above reason, social bookmarking system does not utilize effectively the bookmark information and tagging result. This paper proposes a Web contents ranking algorithm combining bookmarks and tag information, based on preceding research on associative tag extraction by tag clustering. Moreover, we conduct a performance evaluation comparing with existing retrieval methodology for efficiency analysis of our proposed algorithm. As the result, social bookmarking system utilizing bookmark with tag, key point of our research, deduces a effective retrieval results compare with existing systems.

• Journal of Korea Multimedia Society
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• v.14 no.4
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• pp.567-576
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• 2011

In current Web 2.0 environment, one of the most core technology is social bookmarking which users put tags and bookmarks to their interesting Web pages. The main purpose of social bookmarking is an effective information service by use of retrieval, grouping and share based on user's bookmark information and tagging result of their interesting Web pages. But, current social bookmarking system uses the number of bookmarks and tag information separately in information retrieval, where the number of bookmarks stand for user's degree of interest on Web contents, information retrieval, and classification serve the purpose of tag information. Because of above reason, social bookmarking system does not utilize effectively the bookmark information and tagging result. This paper proposes a Web contents ranking algorithm combining bookmarks and tag information, based on preceding research on associative tag extraction by tag clustering. Moreover, we conduct a performance evaluation comparing with existing retrieval methodology for efficiency analysis of our proposed algorithm. As the result, social bookmarking system utilizing bookmark with tag, key point of our research, deduces a effective retrieval results compare with existing systems.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.6
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• pp.915-920
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• 2011

P2P technology is the concept to share resources efficiently in distributed environments that a lot of research is underway. a lot. In these P2P systems, the server to support the contents-information have less overloads than the composed system as the server to have resources generally. In this paper, we suggest a P2P system to support conveniences to choice time for users that were connected with the information of joint-buying based on social network. Social networks based on co-purchasing information and price alerts using the P2P system is provided by the peer, this relay information is provided by the P2P server.

• International Journal of Knowledge Content Development & Technology
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• v.6 no.1
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• pp.5-39
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• 2016

Social networking applications (SNAs) are among the fastest growing web applications of recent years. In this paper, we propose a causal model to assess the success of SNAs, grounded on DeLone and McLean's updated information systems (IS) success model. In addition to their original three dimensions of quality, i.e., system quality, information quality and service quality, we propose that a fourth dimension - networking quality - contributes to SNA success. We empirically examined the proposed research model with a survey of 168 Facebook and 149 Twitter users. The data validates the significant role of networking quality in determining the focal SNA's success. The theoretical and practical implications are discussed.