• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.133-162
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• 2024

The rapid digitalization has highlighted the importance of identifying and managing online resources. Especially, the need for a systematic identification system for the efficient distribution and preservation of digital content is growing. This study aims to respond to these contemporary demands by investigating the current state of identification systems for online resources and exploring more systematic management and utilization methods through linking these systems with legal deposit. To achieve this, the study surveyed the identification systems and their issuance status for online resources and analyzed prior research related to these online resources. Based on the analysis, the proposed strategies for linking with legal deposit can be summarized into three categories: First, to prioritize and enhance the utilization of legal deposit, strategies are required to strengthen the mutual complementarity of deposit and use, to assign priorities to certain deposits, and to increase the usability of deposited materials. Second, as strategies based on international standard numbers for linking with legal deposit, it is necessary to integrate ISBN and UCI in the deposit process, to link international standard resource numbers with deposit, to interconnect metadata between international standard numbers and UCI, to integrate UCI and ICN, and to introduce automation technology for upgrading the deposit system. Third, to effectively implement the aforementioned strategies, policy support is essential. This includes enhancing the role of the Korean Bibliographic Standards Center, strengthening cooperation with publishers, compensating for deposited materials, and increasing awareness and institutional compensation for the legal deposit system.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.39-60
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• 2011

Since the introduction of web 2.0 technology, social network service has been recognized as the foundation of an important future information technology. The advent of web 2.0 has led to the change of content creators. In the existing web, content creators are service providers, whereas they have changed into service users in the recent web. Users share experiences with other users improving contents quality, thereby it has increased the importance of social network. As a result, diverse forms of social network service have been emerged from relations and experiences of users. Social network is a network to construct and express social relations among people who share interests and activities. Today's social network service has not merely confined itself to showing user interactions, but it has also developed into a level in which content generation and evaluation are interacting with each other. As the volume of contents generated from social network service and the number of connections between users have drastically increased, the social network extraction method becomes more complicated. Consequently the following problems for the social network extraction arise. First problem lies in insufficiency of representational power of object in the social network. Second problem is incapability of expressional power in the diverse connections among users. Third problem is the difficulty of creating dynamic change in the social network due to change in user interests. And lastly, lack of method capable of integrating and processing data efficiently in the heterogeneous distributed computing environment. The first and last problems can be solved by using FOAF, a tool for describing ontology-based user profiles for construction of social network. However, solving second and third problems require a novel technology to reflect dynamic change of user interests and relations. In this paper, we propose a novel method to overcome the above problems of existing social network extraction method by applying FOAF (a tool for describing user profiles) and RSS (a literary web work publishing mechanism) to OLAP system in order to dynamically innovate and manage FOAF. We employed data interoperability which is an important characteristic of FOAF in this paper. Next we used RSS to reflect such changes as time flow and user interests. RSS, a tool for literary web work, provides standard vocabulary for distribution at web sites and contents in the form of RDF/XML. In this paper, we collect personal information and relations of users by utilizing FOAF. We also collect user contents by utilizing RSS. Finally, collected data is inserted into the database by star schema. The system we proposed in this paper generates OLAP cube using data in the database. 'Dynamic FOAF Management Algorithm' processes generated OLAP cube. Dynamic FOAF Management Algorithm consists of two functions: one is find_id_interest() and the other is find_relation (). Find_id_interest() is used to extract user interests during the input period, and find-relation() extracts users matching user interests. Finally, the proposed system reconstructs FOAF by reflecting extracted relationships and interests of users. For the justification of the suggested idea, we showed the implemented result together with its analysis. We used C# language and MS-SQL database, and input FOAF and RSS as data collected from livejournal.com. The implemented result shows that foaf : interest of users has reached an average of 19 percent increase for four weeks. In proportion to the increased foaf : interest change, the number of foaf : knows of users has grown an average of 9 percent for four weeks. As we use FOAF and RSS as basic data which have a wide support in web 2.0 and social network service, we have a definite advantage in utilizing user data distributed in the diverse web sites and services regardless of language and types of computer. By using suggested method in this paper, we can provide better services coping with the rapid change of user interests with the automatic application of FOAF.

• Investigative Magnetic Resonance Imaging
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• v.9 no.1
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• pp.24-29
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• 2005

Purpose : Instead of conventional two-dimensional (2-D) visual stimuli, three-dimensional (3-D) visual stimuli with stereoscopic vision were employed for the study of functional Magnetic Resonance Imaging (f-MRI). In this paper f-MRI with 3-D visual stimuli is investigated in comparison with f-MRI with 2-D visual stimuli. Materials and Methods : The anaglyph which generates stereoscopic vision by viewing color coded images with red-blue glasses is used for 3-D visual stimuli. Two-dimensional visual stimuli are also used for comparison. For healthy volunteers, f-MRI experiments were performed with 2-D and 3-D visual stimuli at 3.0 Tesla MRI system. Results : Occipital lobes were activated by the 3-D visual stimuli similarly as in the f-MRI with the conventional 2-D visual stimuli. The activated regions by the 3-D visual stimuli were, however, larger than those by the 2-D visual stimuli by $18\%$. Conclusion : Stereoscopic vision is the basis of the three-dimensional human perception. In this paper 3-D visual stimuli were applied using the anaglyph. Functional MRI was performed with 2-D and 3-D visual stimuli at 3.0 Tesla whole body MRI system. The occipital lobes activated by the 3-D visual stimuli appeared larger than those by the 2-D visual stimuli by about $18\%$. This is due to the more complex character of the 3-D human vision compared to 2-D vision. The f-MRI with 3-D visual stimuli may be useful in various fields using 3-D human vision such as virtual reality, 3-D display, and 3-D multimedia contents.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.482-488
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• 2014

This paper aims to analyze user's emotion automatically by analyzing Twitter, a representative social network service (SNS). In order to create sentiment analysis models by using machine learning techniques, sentiment labels that represent positive/negative emotions are required. However it is very expensive to obtain sentiment labels of tweets. So, in this paper, we propose a sentiment analysis model by using self-training technique in order to utilize "data without sentiment labels" as well as "data with sentiment labels". Self-training technique is that labels of "data without sentiment labels" is determined by utilizing "data with sentiment labels", and then updates models using together with "data with sentiment labels" and newly labeled data. This technique improves the sentiment analysis performance gradually. However, it has a problem that misclassifications of unlabeled data in an early stage affect the model updating through the whole learning process because labels of unlabeled data never changes once those are determined. Thus, labels of "data without sentiment labels" needs to be carefully determined. In this paper, in order to get high performance using self-training technique, we propose 3 policies for updating "data with sentiment labels" and conduct a comparative analysis. The first policy is to select data of which confidence is higher than a given threshold among newly labeled data. The second policy is to choose the same number of the positive and negative data in the newly labeled data in order to avoid the imbalanced class learning problem. The third policy is to choose newly labeled data less than a given maximum number in order to avoid the updates of large amount of data at a time for gradual model updates. Experiments are conducted using Stanford data set and the data set is classified into positive and negative. As a result, the learned model has a high performance than the learned models by using "data with sentiment labels" only and the self-training with a regular model update policy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.855-858
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• 2006

First of all, Developing information technology makes it possible to change a paradigm of all kinds of areas, including an education. Students can choose learning goals and objects themselves and acquire not the accumulation of knowledge but the method of their learning. Moreover, Teachers get to be adviser, and students play a key role in teaming. That is, the subject of leaning is students. Constructivism emphasizes the student-oriented environment of education, which corresponds to the characteristics of hypeimedia. In addition, Internet allows us to make a practical plan for constructivism. Web Based Internet provides us with a proper environment to make constructivism practice md causes an education system to change. Sure Web Based Instruction makes them motivated to learn more, they can gain plenty of information regardless of places or time. Besides, they are able to consult more up-to-date information regarding their learning use hypermedia such as an image, audio, video, and test, and effectively communicate with their instructor through a board, an e-mail, a chatting etc. A school and instructors have been making effort to develop a new model of a teaching method to cope with a new environment change. In this thesis, with 'Design and Implementation of Web Based Instruction Based on Constructivism', providing online learner-oriented and indexed video lesson, learners can get chance of self-oriented learning. In addition, learners doesn't have to cover all contents of a lesson but can choose contents they want to have from a indexed list of a lesson, and they ran search contents they want to have with a 'Keyword Search' on a main page, which can make learners improve learner's achievement.

• Korean Journal of Materials Research
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• v.9 no.3
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• pp.274-281
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• 1999

Usually sputtering and electroless plating methods were used for manufacturing metal-alloy thin film magnetic memory devices. Since electroless plating method has many merits in mass production and product variety com­pared to sputtering method, many researches about electroless plating have been performed in the United State of America and Japan. However, electroless plating method has not been studied frequently in Korea. In these respects the purpose of this research is manufacturing Co-Mn-P alloy thin film on the corning glass 2948 by electroless plating method using sodium hypophosphite as a reductant, and analyzing deposition rate, alloy composition, microstructure, and magnetic characteristics at various pH's and temperatures. For Co-P alloy thin film, the reductive deposition reaction 0$\alpha$urred only in basic condition, not in acidic condition. The deposition rate increased as the pH and temperature increased, and the optimum condition was found at the pH of 10 and the temperature of $80^{\circ}C$. Also magnetic charac­teristics was found to be most excellent at the pH of 9 and the temperature of $70^{\circ}C$, resulting in the coercive force of 8700e and the squareness of 0.78. At this condition, the contents of P was 2.54% and the thickness of the film was $0.216\mu\textrm{m}$. For crystal orientation, we could not observe fcc for $\beta$-Co. On the other hand,(1010), (0002), (1011) orientation of hcp for a-Co was observed. We could confirm the formation of longitudinal magnetization from dominant (1010) and (1011) orientation of Co-P alloy. For Co-Mn-P alloy deposition, coercive force was about 1000e more than that of Co P alloy, but squareness had no difference. For crystal orientation, (l01O) and (lOll) orientation of $\alpha$-Co was dominant as same as that of Co- P alloy. Likewise we could confirm the formation of longitudinal magnetization.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.51-66
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• 2018

As AI (Artificial Intelligence) technologies have been swiftly evolved, a lot of products and services are under development in various fields for better users' experience. On this technology advance, negative effects of AI technologies also have been discussed actively while there exists positive expectation on them at the same time. For instance, many social issues such as trolley dilemma and system security issues are being debated, whereas autonomous vehicles based on artificial intelligence have had attention in terms of stability increase. Therefore, it needs to check and analyse major social issues on artificial intelligence for their development and societal acceptance. In this paper, multi-categorical sentiment analysis is conducted over online public opinion on artificial intelligence after identifying the trending topics related to artificial intelligence for two years from January 2016 to December 2017, which include the event, match between Lee Sedol and AlphaGo. Using the largest web portal in South Korea, online news, news headlines and news comments were crawled. Considering the importance of trending topics, online public opinion was analysed into seven multiple sentimental categories comprised of anger, dislike, fear, happiness, neutrality, sadness, and surprise by topics, not only two simple positive or negative sentiment. As a result, it was found that the top sentiment is "happiness" in most events and yet sentiments on each keyword are different. In addition, when the research period was divided into four periods, the first half of 2016, the second half of the year, the first half of 2017, and the second half of the year, it is confirmed that the sentiment of 'anger' decreases as goes by time. Based on the results of this analysis, it is possible to grasp various topics and trends currently discussed on artificial intelligence, and it can be used to prepare countermeasures. We hope that we can improve to measure public opinion more precisely in the future by integrating empathy level of news comments.

• The Korean Journal of Archival Studies
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• no.42
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• pp.135-183
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• 2014

Korea has a high standard of IT environment to serve exhibit programs through the web with internet propagation and IT technology. However, the web exhibition of public institutions not only seem to introduce off-line exhibitions but also not to invigorate. It is caused by the lack of awareness, the cost of system installation and the lack of professional manpower. In this situation, OMEKA could suggest practical solutions to archives where need their own exhibition through the web. Especially, it would helpful for small record management organizations which are not enough budget and personal. OMEKA is an open source software program for digital collection and contents management. It has an affinity with users unlike traditional archives service programs. It also has been variously used by libraries, museums and schools because of exceptional exhibit functions. In this article, we introduce to the installation of a practical use about OMEKA. Regarding to OMEKA features, we consider it to raise exhibit effects. OMEKA would reduce the cost related to plans of exhibitions because it could display various contents and programs which reflecting characteristics of institutions. In addition, the availability of installation and widespread technological environment would lessen burden of public institutions. Using OMEKA, they would improve service level of public institutions and, make users satisfy. Therefore, they can change the social recognition of public institutions. OMEKA can contribute to various exercises of public records. It is not just the stereotypical system but, serves exhibition and collections with the strategy which each public institution would like to display. After all, it not only to connect to users with producers but also to improve the public image of institutions positively. Then, OMEKA would bring the great result through this interaction between public institutions and users.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.39-53
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• 2013

The emergence of the internet technology and SNS has increased the information flow and has changed the way people to communicate from one-way to two-way communication. Users not only consume and share the information, they also can create and share it among their friends across the social network service. It also changes the Social Media behavior to become one of the most important communication tools which also includes Social TV. Social TV is a form which people can watch a TV program and at the same share any information or its content with friends through Social media. Social News is getting popular and also known as a Participatory Social Media. It creates influences on user interest through Internet to represent society issues and creates news credibility based on user's reputation. However, the conventional platforms in news services only focus on the news recommendation domain. Recent development in SNS has changed this landscape to allow user to share and disseminate the news. Conventional platform does not provide any special way for news to be share. Currently, Social News Service only allows user to access the entire news. Nonetheless, they cannot access partial of the contents which related to users interest. For example user only have interested to a partial of the news and share the content, it is still hard for them to do so. In worst cases users might understand the news in different context. To solve this, Social News Service must provide a method to provide additional information. For example, Yovisto known as an academic video searching service provided time dependent metadata from the video. User can search and watch partial of video content according to time dependent metadata. They also can share content with a friend in social media. Yovisto applies a method to divide or synchronize a video based whenever the slides presentation is changed to another page. However, we are not able to employs this method on news video since the news video is not incorporating with any power point slides presentation. Segmentation method is required to separate the news video and to creating time dependent metadata. In this work, In this paper, a time dependent metadata-based framework is proposed to segment news contents and to provide time dependent metadata so that user can use context information to communicate with their friends. The transcript of the news is divided by using the proposed story segmentation method. We provide a tag to represent the entire content of the news. And provide the sub tag to indicate the segmented news which includes the starting time of the news. The time dependent metadata helps user to track the news information. It also allows them to leave a comment on each segment of the news. User also may share the news based on time metadata as segmented news or as a whole. Therefore, it helps the user to understand the shared news. To demonstrate the performance, we evaluate the story segmentation accuracy and also the tag generation. For this purpose, we measured accuracy of the story segmentation through semantic similarity and compared to the benchmark algorithm. Experimental results show that the proposed method outperforms benchmark algorithms in terms of the accuracy of story segmentation. It is important to note that sub tag accuracy is the most important as a part of the proposed framework to share the specific news context with others. To extract a more accurate sub tags, we have created stop word list that is not related to the content of the news such as name of the anchor or reporter. And we applied to framework. We have analyzed the accuracy of tags and sub tags which represent the context of news. From the analysis, it seems that proposed framework is helpful to users for sharing their opinions with context information in Social media and Social news.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.133-146
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• 2013

While the use of internet is routine nowadays, users receive and share information through a variety of media. Through the use of internet, information delivery media is diversifying from traditional media of one-way communication, such as newspaper, TV, and radio, into media of two-way communication. In contrast of traditional media, blogs enable individuals to directly upload and share news, which can be considered to have a differential speed of information diffusion than news media that convey information unilaterally. Therefore this Study focused on the difference between online news and social media blogs. Moreover, there are variations in the speed of information diffusion because that information closely related to one person boosts communications between individuals. We believe that users' standard of evaluation would change based on the types of information. As well, the speed of information diffusion would change based on the level of proximity. Therefore, the purpose of this study is to examine the differences in information diffusion based on the types of media. And then information is segmentalized and an examination is done to see how information diffusion differentiates based on the types of information. This study used the Bass diffusion model, which has been frequently used because this model has higher explanatory power than other models by explaining diffusion of market through innovation effect and imitation effect. Also this model has been applied a lot in other information diffusion related studies. The Bass diffusion model includes an innovation effect and an imitation effect. Innovation effect measures the early-stage impact, while the imitation effect measures the impact of word of mouth at the later stage. According to Mahajan et al. (2000), Innovation effect is emphasized by usefulness and ease-of-use, as well Imitation effect is emphasized by subjective norm and word-of-mouth. Also, according to Lee et al. (2011), Innovation effect is emphasized by mass communication. According to Moore and Benbasat (1996), Innovation effect is emphasized by relative advantage. Because Imitation effect is adopted by within-group influences and Innovation effects is adopted by product's or service's innovation. Therefore, ours study compared online news and social media blogs to examine the differences between media. We also choose different types of information including entertainment related information "Psy Gentelman", Current affair news "Earthquake in Sichuan, China", and product related information "Galaxy S4" in order to examine the variations on information diffusion. We considered that users' information proximity alters based on the types of information. Hence, we chose the three types of information mentioned above, which have different level of proximity from users' standpoint, in order to examine the flow of information diffusion. The first conclusion of this study is that different media has similar effect on information diffusion, even the types of media of information provider are different. Information diffusion has only been distinguished by a disparity between proximity of information. Second, information diffusions differ based on types of information. From the standpoint of users, product and entertainment related information has high imitation effect because of word of mouth. On the other hand, imitation effect dominates innovation effect on Current affair news. From the results of this study, the flow changes of information diffusion is examined and be applied to practical use. This study has some limitations, and those limitations would be able to provide opportunities and suggestions for future research. Presenting the difference of Information diffusion according to media and proximity has difficulties for generalization of theory due to small sample size. Therefore, if further studies adopt to a request for an increase of sample size and media diversity, difference of the information diffusion according to media type and information proximity could be understood more detailed.