• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.442-448
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• 2023

Artificial Intelligence (AI) technology has recently grown explosively and is being used in a variety of application fields. Accordingly, the number of AI models is rapidly increasing. AI models are adapted and developed to fit a variety of data types, tasks, and environments, and the variety and volume of models continues to grow. The need to share models and collaborate within the AI community is becoming increasingly important. Collaboration is essential for AI models to be shared and improved publicly and used in a variety of applications. Therefore, with the advancement of AI, the introduction of Model Hub has become more important, improving the sharing, reuse, and collaboration of AI models and increasing the utilization of AI technology. In this paper, we collect data on the model hub and analyze the characteristics of the model hub and the AI models provided. The results of this research can be of great help in developing various multimodal AI models in the future, utilizing AI models in various fields, and building services by fusing various AI models.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.97-121
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• 2013

With the growing importance of knowledge for sustainable competitive advantages and innovation in a volatile environment, many researches on knowledge sharing have been conducted. However, previous researches have mostly relied on the questionnaire survey which has inherent perceptive errors of respondents. The current research has drawn the relationship among primary participant behaviors towards the participation level in knowledge sharing, basically from online user behaviors on Wikipedia, a representative community for online knowledge collaboration. Without users' participation in knowledge sharing, knowledge collaboration for creating knowledge cannot be successful. By the way, the editing patterns of Wikipedia users are diverse, resulting in different revisiting periods for the same number of edits, and thus varying results of shared knowledge. Therefore, we illuminated the participation level of knowledge sharing from two different angles of number of edits and revisiting period. The behavioral dimensions affecting the level of participation in knowledge sharing includes the article talk for public discussion and user talk for private messaging, and community registration, which are observable on Wiki platform. Public discussion is being progressed on article talk pages arranged for exchanging ideas about each article topic. An article talk page is often divided into several sections which mainly address specific type of issues raised during the article development procedure. From the diverse opinions about the relatively trivial things such as what text, link, or images should be added or removed and how they should be restructured to the profound professional insights are shared, negotiated, and improved over the course of discussion. Wikipedia also provides personal user talk pages as a private messaging tool. On these pages, diverse personal messages such as casual greetings, stories about activities on Wikipedia, and ordinary affairs of life are exchanged. If anyone wants to communicate with another person, he or she visits the person's user talk page and leaves a message. Wikipedia articles are assessed according to seven quality grades, of which the featured article level is the highest. The dataset includes participants' behavioral data related with 2,978 articles, which have reached the featured article level, with editing histories of articles, their article talk histories, and user talk histories extracted from user talk pages for each article. The time period for analysis is from the initiation of articles until their promotion to the featured article level. The number of edits represents the total number of participation in the editing of an article, and the revisiting period is the time difference between the first and last edits. At first, the participation levels of each user category classified according to behavioral dimensions have been analyzed and compared. And then, robust regressions have been conducted on the relationships among independent variables reflecting the degree of behavioral characteristics and the dependent variable representing the participation level. Especially, through adopting a motivational theory adequate for online environment in setting up research hypotheses, this work suggests a theoretical framework for the participation level of online knowledge sharing. Consequently, this work reached the following practical behavioral results besides some theoretical implications. First, both public discussion and private messaging positively affect the participation level in knowledge sharing. Second, public discussion exerts greater influence than private messaging on the participation level. Third, a synergy effect of public discussion and private messaging on the number of edits was found, whereas a pretty weak negative interaction effect of them on the revisiting period was observed. Fourth, community registration has a significant impact on the revisiting period, whereas being insignificant on the number of edits. Fifth, when it comes to the relation generated from private messaging, the frequency or depth of relation is shown to be more critical than the scope of relation for the participation level.

• Journal of The Korean Association For Science Education
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• v.35 no.3
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• pp.431-442
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• 2015

SSI instruction can be an effective tool to promote key competencies for future citizens. Our assumption of the study is that applying the concept of collective intelligence in the context of SSI learning would facilitate the learning. Thus, we designed and implemented Collective Intelligence-based SSI instruction over almost a year and observed the effects of the instruction on enhancing students' collaboration, information management, critical thinking, and communication skills. Twenty 9th grade students enrolled in a science-gifted program voluntarily participated. Data was collected by administering a questionnaire to examine the skills before, in the middle of, and after the instruction, and by conducting classroom observations and focus student group interviews. The results indicated some degree of improvement in their targeted skills. First, they experienced the expansion of their thoughts by actively sharing information and ideas using the web platform. Second, they became more flexible and open to different points of views in order to accomplish a common goal. Third, they appreciated having independent time and space to explore their own positions on the issues and to search necessary information, and believed that the process encouraged them to more pro-actively participate and communicate in the group debates. Lastly, they positively perceived the values that collaboration with diverse group members could produce.

• Industry Promotion Research
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• v.8 no.2
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• pp.21-27
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• 2023

This study studies the policies and use cases of the government and the financial sector for artificial intelligence, and the future policy tasks of the financial sector. want to derive According to Gartner, noteworthy technologies leading the financial industry in 2022 include 'generative AI', 'autonomous system', 'Privacy Enhanced Computation (PEC) was selected. The financial sector is developing new technologies such as artificial intelligence, big data, and blockchain. Developments are spurring innovation in the financial sector. Data loss due to the spread of telecommuting after the corona pandemic As interests in sharing and personal information protection increase, companies are expected to change in new digital technologies. Global financial companies also utilize new digital technology to develop products or manage and operate existing businesses. I n order to promote process innovation, I T expenses are being expanded. The financial sector utilizes new digital technology to prevent money laundering, improve work efficiency, and strengthen personal information protection. are applying In the era of Big Blur, where the boundaries between industries are disappearing, the competitive edge in the challenge of new entrants In order to preoccupy the market, financial institutions must actively utilize new technologies in their work.

• Journal of Intelligence and Information Systems
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• v.12 no.3
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• pp.127-142
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• 2006

As products become more complex, short-life cycled and customized, the design efforts require more knowledge-intensive, collaborative, coordinating, and information sharing. By sharing knowledge, information, component and process across different families of products, the product realization process will be more efficient, cost-effective and quick-responsive. The purpose of this paper is to propose an ontology-based product family modeling framework. The ideas of product family, ontology and Semantic Web were investigated in depth. A Semantic Web is originally defined as a web of data that can be processed directly or indirectly by machines, which operates intelligently. A Web Ontology Language (OWL) is designed for use by applications that need to process the content of information instead of just presenting information to humans. For the selected cellular phone product family, ontology was constructed and implemented using prot$\acute{e}$g$\acute{e}$-2000.

• Journal of Information Management
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• v.33 no.3
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• pp.87-104
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• 2002

With China Market and strengthening of an international and political position of China, we need to promote exchange and cooperation with China for the supplement of economic vitality and for contriving the contribution of the flow of growth. The necessity of salient traits is needed such as sharing information, training a specialist, network between China Specialists, system establishment of China information DB and sharing China information. Accordingly, KIEP makes the most of limited special manpower and information, and developed China Specialist Forum Website : CSF which will make a stepping stone of systematic, synthetic exchange and cooperation with China. KIEP presented a development direction, comparing and analyzing promptly easy to get the information China Specialists want here, CSF made for mutual exchange of science, trade and the other issue, Taiwan website "a commercial business intelligence network of China and Taiwan", and Singapore "IE Singapore".

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.91-96
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• 2018

Recently, as artificial intelligence technology becomes popular, demand for wireless traffic is rapidly increasing. In order to provide services in response to the increase in demand for wireless traffic, telecommunication companies are generalizing the installation of public APs. In order to provide convenience of using wireless APs between communication companies, it is necessary to share the use of APs in public places to efficiently use wireless resources in a public place, to pre-authenticate between wireless APs in a mobile communication service, So as to increase the convenience of the user. In this paper, we propose to share APs in public places through handoff between APs and pre-authentication between carriers in mobile communication services. The simulation results show that the handoff latency is improved by 35.1% and the bandwidth used by the AP selected by the pre-authentication method can utilize more bandwidth than the method of automatically selecting the AP.

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.7-13
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• 2020

With the recent World Health Organization (WHO) Declaration of Pandemic for Coronavirus Disease-19 (COVID-19), COVID-19 is a global concern and many deaths continue. To overcome this, there is an increasing need for sharing information between countries and countermeasures related to COVID-19. However, due to linguistic boundaries, smooth exchange and sharing of information has not been achieved. In this paper, we propose a Neural Machine Translation (NMT) model specialized for the COVID-19 domain. Centering on English, a Transformer based bidirectional model was produced for French, Spanish, German, Italian, Russian, and Chinese. Based on the BLEU score, the experimental results showed significant high performance in all language pairs compared to the commercialization system.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.275-286
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• 2022

The metaverse platform has been gaining popularity since the pandemic. It facilitates non-face-to-face interaction among creators, users, advertisers, various forms of organizations, and itself. Such interaction has brought light to the new forms of economy, which is called the "creator economy." By providing the virtual space, easy tools, and methods, the platform allows the creators to produce value for the users in the forms of virtual items, content, and experiences. At the same time, it provides audiences to the organizations that need attention. In the course, the platform and the creators generate revenue. Among the diverse revenue sources, this study focuses on revenue generated from advertising and studies how the revenue sharing between the platform and the creator is affected by the abilities of the metaverse platform. With an analysis of the analytical model, we show that if the platform has the ability to reduce advertising avoidance, it can reduce the revenue share of the creator without discouraging the creator from making the proper effort in content creation. Also, as the platform provides effective tools and methods for quality content creation, it can reduce the revenue share of the creator without damaging the creator's required motivation. The ability of the platform in increasing advertising effectiveness helps it to reduce the revenue share of the creator as well.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.377-379
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• 2022

POI refers to the point of Interest in Location-Based Social Networks (LBSNs). With the rapid development of mobile devices, GPS, and the Web (web2.0 and 3.0), LBSNs have attracted many users to share their information, physical location (real-time location), and interesting places. The tremendous demand of the user in LBSNs leads the recommendation systems (RSs) to become more widespread attention. Recommendation systems assist users in discovering interesting local attractions or facilities and help social network service (SNS) providers based on user locations. Therefore, it plays a vital role in LBSNs, namely POI recommendation system. In the machine learning model, most of the training data are stored in the centralized data storage, so information that belongs to the user will store in the centralized storage, and users may face privacy issues. Moreover, sharing the information may have safety concerns because of uploading or sharing their real-time location with others through social network media. According to the privacy concern issue, the paper proposes a recommendation model to prevent user privacy and eliminate traditional RS problems such as cold-start and data sparsity.