• Journal of Korean Society of Archives and Records Management
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• v.22 no.1
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• pp.61-82
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• 2022

This study aims to investigate the factors influencing the learning satisfaction of records management cyber education that is opened and operated by the National Archives of Korea, as well as to improve the quality of cyber education program. Cyber education consisted of an introductory course, an intensive course, and a liberal arts course. As the major factors for learning satisfaction, "validity of content structure, interaction between professors and learners, learning motivation, active learning attitude, ease of use environment, and level of organizational support" were set. An online survey was conducted on the learning satisfaction according to the curriculum of each course. The survey was conducted to 107 institutions with specialized records management personnel, and additional in-depth interviews were also conducted. The survey analysis consisted of factor analysis, independent sample T-test, analysis of variance (ANOVA), correlation analysis, and multiple regression analysis. As a result of the study, the factors influencing learning satisfaction were found in the order of interaction between professors and learners, learning motivation, and validity of content structure.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.817-824
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• 2003

We employed a hierarchical document classification method to classify a massive collection of electronic medical records(EMR) written in both Korean and English. Our experimental system has been learned from 5,000 records of EMR text data and predicted a newly given set of EMR text data over 68% correctly. We expect the accuracy rate can be improved greatly provided a dictionary of medical terms or a suitable medical thesaurus. The classification system might play a key role in some clinical decision support systems and various interpretation systems for clinical data.

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.321-344
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• 2017

Research on automatic classification of records and documents has been conducted for a long time. Recently, artificial intelligence technology has been developed to combine machine learning and deep learning. In this study, we first looked at the process of automatic classification of documents and learning method of artificial intelligence. We also discussed the necessity of applying artificial intelligence technology to records management using various cases of machine learning, especially supervised methods. And we conducted a test to automatically classify the public records of the Seoul metropolitan government into BRM using ETRI's Exobrain, based on supervised machine learning method. Through this, we have drawn up issues to be considered in each step in records management agencies to automatically classify the records into various classification schemes.

• Journal of Korean Society of Archives and Records Management
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• v.22 no.4
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• pp.129-149
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• 2022

Records have temporal characteristics, including the past and present; linguistic characteristics not limited to a specific language; and various types categorized in a complex way. Processing records such as text, video, and audio in the life cycle of records' creation, preservation, and utilization entails exhaustive effort and cost. Primary natural language processing (NLP) technologies, such as machine translation, document summarization, named-entity recognition, and image recognition, can be widely applied to electronic records and analog digitization. In particular, Korean deep learning-based NLP technologies effectively recognize various record types and generate record management metadata. This paper provides an overview of Korean NLP technologies and discusses considerations for applying NLP technology in records management. The process of using NLP technologies, such as machine translation and optical character recognition for digital conversion of records, is introduced as an example implemented in the Python environment. In contrast, a plan to improve environmental factors and record digitization guidelines for applying NLP technology in the records management field is proposed for utilizing NLP technology.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.239-253
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• 2024

This research applies both point-wise and pair-wise learning strategies within the learning-to-rank (LTR) framework to predict horse race rankings in Seoul. Specifically, for point-wise learning, we employ a linear model and random forest. In contrast, for pair-wise learning, we utilize tools such as RankNet, and LambdaMART (XGBoost Ranker, LightGBM Ranker, and CatBoost Ranker). Furthermore, to enhance predictions, race records are standardized based on race distance, and we integrate various datasets, including race information, jockey information, horse training records, and trainer information. Our results empirically demonstrate that pair-wise learning approaches that can reflect the order information between items generally outperform point-wise learning approaches. Notably, CatBoost Ranker is the top performer. Through Shapley value analysis, we identified that the important variables for CatBoost Ranker include the performance of a horse, its previous race records, the count of its starting trainings, the total number of starting trainings, and the instances of disease diagnoses for the horse.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.12
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• pp.1657-1664
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• 2018

This paper proposes a decision making scheme for choosing the best move at each state of game in order to implement an artificial intelligence othello game player. The proposed decision making scheme predicts the various possible states of the game when the game has progressed from the current state, evaluates the degree of possibility of winning or losing the game at the states, and searches the best move based on the evaluation. In this paper, we generate learning data by decomposing the records of professional players' real game into states, matching and accumulating winning points to the states, and using the Artificial Neural Network that learned them, we evaluated the value of each predicted state and applied the Minimax search to determine the best move. We implemented an artificial intelligence player of the Othello game by applying the proposed scheme and evaluated the performance of the game player through games with three different artificial intelligence players.

• Journal of IKEEE
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• v.23 no.4
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• pp.1187-1194
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• 2019

This paper proposes a CNN architecture as value function network of an artificial intelligence Othello game agent and its learning scheme using reinforcement learning algorithm. We propose an approach to construct the value function network by using CNN to learn the records of professional players' real game and an approach to enhance the network parameter by learning from self-play using reinforcement learning algorithm. The performance of value function network CNN was compared with existing ANN by letting two agents using each network to play games each other. As a result, the winning rate of the CNN agent was 69.7% and 72.1% as black and white, respectively. In addition, as a result of applying the reinforcement learning, the performance of the agent was improved by showing 100% and 78% winning rate, respectively, compared with the network-based agent without the reinforcement learning.

• Journal of Korean Society of Archives and Records Management
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• v.17 no.3
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• pp.115-138
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• 2017

Electronic record types are becoming diverse, and "composite electronic records," which are made up of various types of electronic records associated with functionality or user interaction that does not exist in current electronic document formats, are increasing. To ensure a continuous access to composite electronic records, metadata construction is a prerequisite for electronic records archiving. In this paper, we propose a metadata that can support archiving of composite electronic records associated with interactive functionality. The common elements were derived from an analysis of both domestic and international file format registry projects, and metadata elements related to functional requirements were identified from the analysis of the records on nursing education e-learning contents. We proposed the metadata elements for archiving composite electronic records, which consist of 25 high-level elements and 138 subelements.

• Journal of Korean Society of Archives and Records Management
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• v.8 no.1
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• pp.143-165
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• 2008

This study is concerned with educational services provided for archives with a focus on programs for teachers and students in the classroom. The purpose of this study is to develop the archival-resource based learning model. And the other purpose is to find out the influence of the archival-resource based learning. The researcher and teachers designed two lessen plans for archival-resource based learning and general learning. To compare with the archival-resource based learning and the general learning, the researcher divided into two comparison classes of 6th graders of two elementary schools. Statistical analysis was conducted by analysis of covariance using SPSS WIN 12.0 for t-test.

• The Korean Journal of Archival Studies
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• no.51
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• pp.89-132
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• 2017

The presidential records reflect the era of the times, and it has valuable evidence to support the administrative transparency and accountability of government operations. People's interest in the presidential records increased in response to its recent leak. The presidential archives were moved to Sejong in line with its desire to provide public-friendly services. This study will help users access the archives and utilize archiving information. The Ministry of Education introduced the free learning semester, which all middle schools have began conducting since 2016. The free learning semester provides an environment where education can be provided by external organizations. As middle school students are still unfamiliar with archives, the free learning semester provides a good environment for accessing archives and records. Although it serves as an opportunity to publicize archives, existing related studies are insufficient. This study aims to develop the free learning semester program using the presidential archives and records for middle school students during the free learning semester based on the analysis of the domestic and foreign archives education program. This study shows a development of the education program using presidential archives and records through literature research, domestic and foreign case analysis, and expert interview. First, through literature research, this research understood the definition of the free learning semester as well as its types. In addition, this research identified the four types of the free learning semester education program that can be linked to the presidential archives. Second, through website analysis and the information disclosure system, this research investigated domestic and foreign cases of the education program. A total of 46 education programs of institutions were analyzed, focusing on student-led education programs in the foreign archives as well as the education programs of the free learning semester in domestic libraries and archives. Third, based on these results, This study proposed four types of free learning semester education programs using the presidential archives and records, and provided concrete examples.