• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.4
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• pp.73-92
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• 2022

This study intends to design a model that can effectively service policy data necessary for the implementation of new national agenda in order to provide high-quality policy information services that go beyond those of the existing Policy Information Portal (POINT) of National Sejong Library. To this end, it was determined that providing an integrated search environment, in lieu of data search through individual access, was necessary. Subsequently, four possible models for a national agenda service model were presented. First, designing a computerized system for both interface and electronic information source aspects was proposed for the national agenda service system operation. Second, designing the Linked Open Data system and the time-series service system for national policy information, providing the translation service of overseas original data, and securing the researcher's desired data were presented for the national agenda service information source operation. Third, strengthening public relations for policy users, building and promoting the site brand, operating SNS channels, and reinforcing the activation of auxiliary materials and the accessibility of external services were proposed for public relations of national agenda service. Fourth, expanding the information network with Open API, cloud service, and overseas libraries was proposed for collaborating and cooperating with the agenda service.

• The Korean Journal of Archival Studies
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• no.1
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• pp.137-188
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• 2000

Korea was highly successful in maintaining a strong tradition of record preservation. However, Japanese imperialism and the Korean war over this century has seen a huge quantity of these once plentiful records either destroyed or relocated overseas. Many of Korea records remain in the custody of foreign archival institutions. Additionally, many records of foreign states concerned with korean affairs, for example, records of the Department of state, in the U.S.A., are of great relevance to Korean modern history. These records which exist in foreign countries are a necessary and invaluable resource in the advancement of Korea studies. After the 1980s, as research interest in Korean modern history increased gradually, much historical material related to Korea was extensively introduced, removed, collected from the U.S.A., Japan, Russia and China etc. by the efforts of pioneering scholars and institutions. Several attempts at collating and publishing this material have been made. Despite this encouraging result, individual scholars and institutions's efforts face problems in relation to removal of records. Firstly, it is repeated nonproductively to remove and collect the same records, for we didn't establish a comprehensive information system, through which the condition of foreign record removal and management is able to be administrated. Secondly, there is no system for arrangement, preservation, use of removed records. For example, finding aids, such as inventory, register, description, isn't prepared for user. A user may usually not understand an accurate context of their creation, preservation removal. Thirdly, almost institution has arranged the removed records among other materials and books. Each institution has a different classification criteria, too. These conditions seem to make a difficulty in national management. This study investigated how the materials for Korea history which has been removed from foreign countries should be managed for effective preservation and use. For these purpose, we investigated the present conditions of removal and management of these materials. Also, we investigated examples of the foreign state, U.S.A. and Japan to have a idea for removal and management policy. Then, This study propose a establishment of information network system as management policy. To administrate removing and managing records effectively, an idea that records belong to the public should be accepted commonly. The policy for management of the record is followings. Firstly, unification of classification is necessary. The records which were removed from foreign countries had better to be classified according to their origins of states and institutions. Secondly, Finding aids should be prepared for user. There are many accession aids such as catalog, register, inventory for user in archives. This will be a efficient method for management. When a record is removed, a card for description of contents must be composed. Thirdly, a digital input and network system establishment is necessary. It will help to manage a condition of removed records. A digital input and management system establishment is not just a project of digitalizing records. At present, various finding aids need to be introduced to make a database for records and archives. An search using only 'search engine' may make a difficulty in finding materials because such method is apt to have too much or little result. So, classification, arrangement, description, response-service should be integrated in these system. The recent technical advancement give a opportunity to realize this idea. Above all, these procedure should be archival process.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.149-169
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• 2018

Korea is currently accumulating a large amount of data in public institutions based on the public data open policy and the "Government 3.0". Especially, a lot of data is accumulated in the tourism field. However, the academic discussions utilizing the tourism data are still limited. Moreover, the openness of the data of restaurants, hotels, and online tourism information, and how to use SNS Big Data in tourism are still limited. Therefore, utilization through tourism big data analysis is still low. In this paper, we tried to analyze influencing factors on foreign tourists' satisfaction in Korea through numerical data using data mining technique and R programming technique. In this study, we tried to find ways to revitalize the tourism industry by analyzing about 36,000 big data of the "Survey on the actual situation of foreign tourists from 2013 to 2015" surveyed by the Korea Culture & Tourism Research Institute. To do this, we analyzed the factors that have high influence on the 'Satisfaction', 'Revisit intention', and 'Recommendation' variables of foreign tourists. Furthermore, we analyzed the practical influences of the variables that are mentioned above. As a procedure of this study, we first integrated survey data of foreign tourists conducted by Korea Culture & Tourism Research Institute, which is stored in the tourist information system from 2013 to 2015, and eliminate unnecessary variables that are inconsistent with the research purpose among the integrated data. Some variables were modified to improve the accuracy of the analysis. And we analyzed the factors affecting the dependent variables by using data-mining methods: decision tree(C5.0, CART, CHAID, QUEST), artificial neural network, and logistic regression analysis of SPSS IBM Modeler 16.0. The seven variables that have the greatest effect on each dependent variable were derived. As a result of data analysis, it was found that seven major variables influencing 'overall satisfaction' were sightseeing spot attraction, food satisfaction, accommodation satisfaction, traffic satisfaction, guide service satisfaction, number of visiting places, and country. Variables that had a great influence appeared food satisfaction and sightseeing spot attraction. The seven variables that had the greatest influence on 'revisit intention' were the country, travel motivation, activity, food satisfaction, best activity, guide service satisfaction and sightseeing spot attraction. The most influential variables were food satisfaction and travel motivation for Korean style. Lastly, the seven variables that have the greatest influence on the 'recommendation intention' were the country, sightseeing spot attraction, number of visiting places, food satisfaction, activity, tour guide service satisfaction and cost. And then the variables that had the greatest influence were the country, sightseeing spot attraction, and food satisfaction. In addition, in order to grasp the influence of each independent variables more deeply, we used R programming to identify the influence of independent variables. As a result, it was found that the food satisfaction and sightseeing spot attraction were higher than other variables in overall satisfaction and had a greater effect than other influential variables. Revisit intention had a higher ${\beta}$ value in the travel motive as the purpose of Korean Wave than other variables. It will be necessary to have a policy that will lead to a substantial revisit of tourists by enhancing tourist attractions for the purpose of Korean Wave. Lastly, the recommendation had the same result of satisfaction as the sightseeing spot attraction and food satisfaction have higher ${\beta}$ value than other variables. From this analysis, we found that 'food satisfaction' and 'sightseeing spot attraction' variables were the common factors to influence three dependent variables that are mentioned above('Overall satisfaction', 'Revisit intention' and 'Recommendation'), and that those factors affected the satisfaction of travel in Korea significantly. The purpose of this study is to examine how to activate foreign tourists in Korea through big data analysis. It is expected to be used as basic data for analyzing tourism data and establishing effective tourism policy. It is expected to be used as a material to establish an activation plan that can contribute to tourism development in Korea in the future.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.64-76
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• 2009

Recently, the ubiquitous environment and the practical technology associated with it become more popular topic along with the rapid development of wireless technologies. The necessity of the automated system based on the ubiquitous environment has been increasing when the concept of the ubiquitous is integrated into the fields of existing IT. Also, the necessity of formulating a power-saving plan on large buildings and public institutions is gathering strength because of a raise in exchange rates and high oil prices. In this paper, to efficiently manage the power consumption of the electronic machine such as electric lights, electric heaters, and air conditioners in a building, power-saving manage- ment system using RFID/USN technologies is proposed. Proposed system controls the electric machine and monitor it's condition by RFID and collects the real time information about the surrounding and the power consumption of the electric machine by USN. Especially, proposed system analyzes the real time information and supports the intelligent scheduler with the best power-saving. Finally, this paper shows the difference between proposed system and existing system and establishes thereality of our system through experiments in variety environments.

• The Journal of Korean Association of Computer Education
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• v.17 no.6
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• pp.93-102
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• 2014

A mobile office environment using mobile devices, such as tablet PC, mobile phone is gradually increased in enterprises, banking and public institutions etc which is no limitation on places. It occurs advanced and persist security threats that are required effective security management policy and technical solution to be secure. For BYOD (Bring Your Own Device) environment, technical security management solutions of network control based, MDM (Mobile Device Management), MAM (Mobile Application Management), MCM (Mobile Contents Management) were released, evolved and mixed used. In perspective of integrated security management solution, mobile security product should be selected to consider user experience and environment and correct quality evaluation model of product is needed which is provided standards and guidance on the selection criteria when it was introduced. In this paper, the most widely used MDM solution is selected to take a look at its features and it was reviewed the product attributes with related international standard ISO/IEC25010 software quality attributes. And then it was derived evaluation elements and calculated the related metrics based on the quality analysis model. For the verification of quality evaluation model, security checks list and testing procedures were established; it applied metrics and analyzed the testing result through scenario based case study.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.3
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• pp.7-15
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• 2019

Cloud computing markets are rapidly growing as cost savings and business innovation are being carried out through ICT worldwide. In line with this paradigm, the nation is striving to introduce cloud computing in various areas, including the public sector and defense sector, through various research. In the defense sector, DIDC was established in 2015 by integrating military, naval, air and military computing centers, and it provides cloud services in the form of IaaS to some systems in the center. In DIDC and various future cloud defense systems, It is an important issue to ensure availability in cloud defense systems in the defense sector because system failures such as network delays and system resource failures are directly linked to the results of battlefields. However, ensuring the highest levels of availability for all systems in the defense cloud can be inefficient, and the efficiency that can be gained from deploying a cloud system can be reduced. In this paper, we classify and define the level of availability of defense cloud systems step by step, and propose the strategy of introducing Erasure coding and failure acceptance systems, and disaster recovery system technology according to each level of availability acquisition.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.