• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.169-178
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• 2020

The reductions of troops/human resources, and improvement in combat power have made Korean Department of Defense actively adapt 4th Industrial Revolution technology (Artificial Intelligence, Big Data). The defense information system has been developed in various ways according to the task and the uniqueness of each military. In order to take full advantage of the 4th Industrial Revolution technology, it is necessary to improve the closed defense datamanagement system.However, the establishment and usage of data standards in all information systems for the utilization of defense big data and artificial intelligence has limitations due to security issues, business characteristics of each military, anddifficulty in standardizing large-scale systems. Based on the interworking requirements of each system, data sharing is limited through direct linkage through interoperability agreement between systems. In order to implement smart defense using the 4th Industrial Revolution technology, it is urgent to prepare a system that can share defense data and make good use of it. To technically support the defense, it is critical to develop Multi Repository Meta-Data Management (MRMM) that supports systematic standard management of defense data that manages enterprise standard and standard mapping for each system and promotes data interoperability through linkage between standards which obeys the Defense Interoperability Management Development Guidelines. We introduced MRMM, and implemented by using vocabulary similarity using machine learning and statistical approach. Based on MRMM, We expect to simplify the standardization integration of all military databases using artificial intelligence and bigdata. This will lead to huge reduction of defense budget while increasing combat power for implementing smart defense.

• Journal of Korean Home Economics Education Association
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• v.26 no.3
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• pp.91-112
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• 2014

The purpose of this study is to analyze how the elements of activating happiness education suggested by Noddings is reflected in the Home Economics part of Middle School Technology-Home Economics Textbook Volume 2 of 2009 Curriculum Revision. The introduction style of unit, sub-unit, and small chapter, the objectives, the body contents, the activity resources, the tables/diagrams/pictures, the supplementry and advancedl materials, and the wrap-up and evaluation of sub-unit and units of Home Economics part of Technology Home Economics textbook volume 2 were analyzed. Noddings suggested the elements for activating happiness education in five areas of personal life sector including 'home making', 'place and nature', 'parenting', 'chracter and spiriual experiences', and 'growth of interpersonal relationships' and two areas of public one including 'preperation for work' and 'community, democracy and voluntary activities'. The specific elements in seven sectors of activating happiness education were extracted using the content analysis. How the elements of those suggested by Noddings were reflected in the various parts of the textbook were analyzed in terms of the closeness of approaches, contents, and procedures between Noddings's and textbook. The major findings of this study were as follows: 1. The degree to which the elements of activating happiness education were reflected in the textbook differed by each unit. The elements of activating happiness education were reflected the most frequently in the unit of 'Unit of Practice of Eco-friendly Family Life' and the least frequently in the unit of 'Unit of Career and Life Planning'. 2. The Home Economics units of Technology Home Economics textbooks 1&2 reflects the factors of personal life and public life that Noddings suggested for activating happiness. However, personal life-related factors are relatively more reflected in the units than the public life-related factors. 3. Although the elements of activating happiness education were generally reflected in all the elements of a textbook, these elements were relatively more reflected in the Unit Introduction, Sub-unit Introduction, Chapter and Introduction, Objectives, body contents and tables/diagrams/pictures.

• Korean Journal of Heritage: History & Science
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• v.53 no.3
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• pp.164-183
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• 2020

In the textile culture of the Joseon Dynasty, the historic record of Banpo is fragmentary and contains many missing details. The main reason is a lack of associated literature, and it is also significant that the actual substance used is not clear at present. Banpo is a kind of cotton, but this has not been confirmed in the traditional textiles that are currently handed down. The word Ban [斑] in Banpo means "stain", and the letter Po [布] means "fabric". At the border of white discourse, Banpo did not receive attention as a research topic. This study is an attempt to restore some of the textile culture of the Joseon Dynasty through Banpo. Banpo is not just limited to the Joseon Dynasty; it is an important material for examining the development of textile culture and exchange in East Asia. This study was broadly divided into three parts. First, the record and meaning of Banpo during the Joseon Dynasty were examined. Records of Banpo can be seen from the early Joseon period during King Sejo and Seongjong, and the production and actual use of Banpo have been confirmed. Banpo was maintained until the beginning of the 20^th century, but is no longer observed. Banpo is a woven fabric made of cotton yarn dyed in many colors and has appeared in Southeast Asia since ancient times. In East Asia, there are other fabrics similar to Banpo, such as Ho [縞], Sum [纖], and Chim [綅]. In particular, the correlation between Banpo and Ho is an important link in understanding Banpo in the Joseon Dynasty. Second, the meaning of Banpo was examined from various angles through comprehensive analysis of Chinese and Japanese literature records and cases. The appearance and development of Banpo moved in sync with the period when cotton was introduced into East Asia. In East Asia, cotton was introduced and produced in earnest from the end of the Song Dynasty to the beginning of the Yuan Dynasty, and the meaning of Banpo was diversified. In China, the name of Banpo was changed to Hwapo [花布], Gizapo [碁子布], Gizahwapo [棋子花布], etc. Japan was late to introduce cotton and developed it in acceptance of the changed meaning. In Japan, use of the name Banpo is not on record, but a Ryujo [柳條] fabric of the same type as banpo has been identified. This Ryujo is the same concept as Ho and Hwapo, and later merged into Ho. Names such as Ho, Hwapo, Banpo, etc. were used differently in each country, but the form was shared across East Asia. Third, based on the meaning of Banpo shared in East Asia, the format of Banpo in the Joseon Dynasty was classified. The format of Banpo in the Joseon Dynasty can be divided into grid and striped versions. The name Banpo disappeared over time, but the form remained and was passed down until recently. I hope that this study will help restore Banpo in the future.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.21-41
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• 2010

This paper proposes a system that can serve users with appropriate search results through real time filtering, and implemented adaptive user profiling based personalized information retrieval system(PIRS) using users' implicit feedbacks in order to deal with the problem of existing search systems such as Google or MSN that does not satisfy various user' personal search needs. One of the reasons that existing search systems hard to satisfy various user' personal needs is that it is not easy to recognize users' search intentions because of the uncertainty of search intentions. The uncertainty of search intentions means that users may want to different search results using the same query. For example, when a user inputs "java" query, the user may want to be retrieved "java" results as a computer programming language, a coffee of java, or a island of Indonesia. In other words, this uncertainty is due to ambiguity of search queries. Moreover, if the number of the used words for a query is fewer, this uncertainty will be more increased. Real-time filtering for search results returns only those results that belong to user-selected domain for a given query. Although it looks similar to a general directory search, it is different in that the search is executed for all web documents rather than sites, and each document in the search results is classified into the given domain in real time. By applying information filtering using real time directory classifying technology for search results to personalization, the number of delivering results to users is effectively decreased, and the satisfaction for the results is improved. In this paper, a user preference profile has a hierarchical structure, and consists of domains, used queries, and selected documents. Because the hierarchy structure of user preference profile can apply the context when users perfomed search, the structure is able to deal with the uncertainty of user intentions, when search is carried out, the intention may differ according to the context such as time or place for the same query. Furthermore, this structure is able to more effectively track web documents search behaviors of a user for each domain, and timely recognize the changes of user intentions. An IP address of each device was used to identify each user, and the user preference profile is continuously updated based on the observed user behaviors for search results. Also, we measured user satisfaction for search results by observing the user behaviors for the selected search result. Our proposed system automatically recognizes user preferences by using implicit feedbacks from users such as staying time on the selected search result and the exit condition from the page, and dynamically updates their preferences. Whenever search is performed by a user, our system finds the user preference profile for the given IP address, and if the file is not exist then a new user preference profile is created in the server, otherwise the file is updated with the transmitted information. If the file is not exist in the server, the system provides Google' results to users, and the reflection value is increased/decreased whenever user search. We carried out some experiments to evaluate the performance of adaptive user preference profile technique and real time filtering, and the results are satisfactory. According to our experimental results, participants are satisfied with average 4.7 documents in the top 10 search list by using adaptive user preference profile technique with real time filtering, and this result shows that our method outperforms Google's by 23.2%.

• Sim-seong Yeon-gu
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• v.28 no.1
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• pp.50-87
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• 2013

C. G. Jung believed that universal and basic condition of human's Unconscious comes out from Märchen or mythology. We can easily experience these universality of human nature in dreams. Therefore, It is very important to interpret mythogens that appear in myths and märchen in analytical psychology to understand these 'big dreams' which could be seen in clinical practice. As I was interested in interpreting myths in analytic psychology, I tried to find universality of archetypes in Korea's traditional folk tales and took note of the birth myth of Hyeokgeose, the founder of Shilla dynasty, while examining the chater of the Unsual in history in the Heritage of the Three Kingdoms. Shilla was founded earlier than two other countries, but it was located in the very south of the Korean Peninsula, and it was behind times in politically, militarily, and culturally compare to Goguryeo and Baekje. However, Shilla achieved unifying the Three Kingdoms and it lasted 1000 years, the longest unified history in Korean history. I tried to examine archetypes in the birth myth if there are any backgrounds that are related to finding a Shilla Kingdom. It is noted that myth of the founder of Korean Peninsula's small Kingdom Shilla has complete story from before the birth to birth, birth of spouse, growth, marriage, accession, governing, death, after death, and succession. Symbols such as numbers 1, 3, 5, 6, 7, 13 and 61, various azimuthes including north, west, south, east, and central, animals like tiger, white horse, hen, dragon, phoenix, and snakes, natures like main symbol egg, rock, gourd, lightening, spring water, stream, tree, forest, mountain, iron and goddess-image like seon-do Holy Mother gradually appears in the myth. These symbols could show a meaning of human experience such as birth of Conscious, growth and development of paternal and maternal love, and story of regeneration and extinction. Moreover, It could be seen as these progress eternally continues in next generation. I have found out that a word, a sentence or stories that looks meaningless in myth revealed its true symbolical meaning. In addition, interaction between Unconscious and Conscious repeats in different forms, and expressed in layered.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.141-156
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• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.