• 한국IT서비스학회지
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• 제22권3호
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• pp.29-47
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• 2023

With the recent advancement of information and communication technologies such as artificial intelligence, big data, cloud computing, and 5G, data is being produced and digitized in unprecedented amounts. As a result, data has emerged as a critical resource for the future economy, and overseas countries have been revising laws for data protection and utilization. In Korea, the 'Data 3 Act' was revised in 2020 to introduce institutional measures that classify personal information, pseudonymized information, and anonymous information for research, statistics, and preservation of public records. Among them, it is expected to increase the added value of data by combining pseudonymized personal information, and to this end, "the Expert Data Combination Agency" and "the Expert Data Agency" (hereinafter referred to as the Expert Data Processing Agency) system were introduced. In comparison to these domestic systems, we would like to analyze similar overseas systems, and it was recently confirmed that the Vermont government in the United States enacted the first "Data Broker Act" in the United States as a measure to protect personal information held by data brokers. In this study, we aim to compare and analyze the roles and functions of the "Expert Data Processing Agency" and "Data Broker," and to identify differences in designated standards, security measures, etc., in order to present ways to contribute to the activation of the data economy and enhance information protection.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2022년도 춘계학술발표대회
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• pp.366-369
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• 2022

The glut of information aggravated the process of data analysis and other procedures including data mining. Many algorithms were devised in Big Data and Data Mining to solve such an intricate problem. In this paper, we conducted research about the comparison of several similarity measures and community detection algorithms in collaborative filtering for movie recommendation systems. Movielense data set was used to do an empirical experiment. We applied three different similarity measures: Cosine, Euclidean, and Pearson. Moreover, betweenness and eigenvector centrality were used to detect communities from the network. As a result, we elucidated which algorithm is more suitable than its counterpart in terms of recommendation accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권12호
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• pp.4062-4080
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• 2022

COVID-19, a highly infectious disease, has affected the globe tremendously since its outbreak during late 2019 in Wuhan, China. In order to respond to the pandemic, governments around the world introduced a variety of public health measures including contact-tracing, a method to identify individuals who may have come into contact with a confirmed COVID-19 patient, which usually leads to quarantine of certain individuals. Like many other governments, the South Korean health authorities adopted public health measures using latest data technologies. Key data technology-based quarantine measures include:(1) Electronic Entry Log; (2) Self-check App; and (3) COVID-19 Wristband, and heavily relied on individual's personal information for contact-tracing and self-isolation. In fact, during the early stages of the pandemic, South Korea's strategy proved to be highly effective in containing the spread of coronavirus while other countries suffered significantly from the surge of COVID-19 patients. However, while the South Korean COVID-19 policy was hailed as a success, it must be noted that the government achieved this by collecting and processing a wide range of personal information. In collecting and processing personal information, the data minimum principle - one of the widely recognized common data principles between different data protection laws - should be applied. Public health measures have no exceptions, and it is even more crucial when government activities are involved. In this study, we provide an analysis of how the governments around the world reacted to the COVID-19 pandemic and evaluate whether the South Korean government's digital quarantine measures ensured the protection of its citizen's right to privacy.

• 대한교통학회지
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• 제27권3호
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• pp.59-70
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• 2009

본 연구는 실시간 주행환경에서 교통사고를 유발할 수 있는 위험한 교통상황을 검지하고 경고정보를 운전자에게 제공하여 운전자의 회피 행동을 효율적으로 유도할 수 있는 경고정보시스템을 제안하였다. 교통사고 개연성을 계량화해서 나타낼 수 있는 Surrogate Safety Measure(SSM)를 도출하여 제안한 시스템의 구현을 위한 정보처리 및 가공기법을 개발하였다. 제안된 알고리즘을 통해 생성된 경고정보는 긴급영향권과 일반영향권으로 구분되어 제공 될 수 있다. 각 영향권에서 차별화된 경고정보 제공이 가능하도록 하는 임계값 결정방법론을 제시하였다. 본 연구에서 새롭게 제안하는 경고정보시스템은 고속도로 교통사고 예방을 위한 교통류 관리를 위해 효과적으로 활용될 것으로 기대된다.

• Journal of Information Processing Systems
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• 제17권1호
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• pp.107-123
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• 2021

In an online shopping site or offline store, products purchased by each customer over time form the purchase history of the customer. Also, in most retailers, products have a product taxonomy, which represents a hierarchical classification of products. Considering the product taxonomy, the lower the level of the category to which two products both belong, the more similar the two products. However, there has been little work on similarity measures for sequences considering a hierarchical classification of elements. In this paper, we propose new similarity measures for purchase histories considering not only the purchase order of products but also the hierarchical classification of products. Unlike the existing methods, where the similarity between two elements in sequences is only 0 or 1 depending on whether two elements are the same or not, the proposed method can assign any real number between 0 and 1 considering the hierarchical classification of elements. We apply this idea to extend three existing representative similarity measures for sequences. We also propose an efficient computation method for the proposed similarity measures. Through various experiments, we show that the proposed method can measure the similarity between purchase histories very effectively and efficiently.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 춘계학술발표대회
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• pp.135-138
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• 2018

In Japan, 24th May 2013, the Act on the Use of Numbers to Identify a Specific Individual in the Administrative Procedure (From now on referred to as the My Number Act) had raised. My Number system is used to confirm that information on individuals possessed by multiple agencies such as administrative agencies and local governments are information of the same person. In this paper, we analyzed the all item assessment report of the Specific Personal Information Protection Assessment conducted in local governments in Japan, etc. We investigated two directions: (1) Adequacy of risk assessment and measures, (2) Reuse of the Assessment Report.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1438-1444
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• 2018

Recently, with the development of Internet technologies and propagation of smart devices, use of microblogs such as Facebook, Twitter, and Instagram has been rapidly increasing. Many users check for new information on microblogs because the content on their timelines is continually updating. Therefore, clustering algorithms are necessary to arrange the content of microblogs by grouping them for a user who wants to get the newest information. However, microblogs have word limits, and it has there is not enough information to analyze for content clustering. In this paper, we propose a semantic-based K-means clustering algorithm that not only measures the similarity between the data represented as a vector space model, but also measures the semantic similarity between the data by exploiting the TagCluster for clustering. Through the experimental results on the RepLab2013 Twitter dataset, we show the effectiveness of the semantic-based K-means clustering algorithm.

• Journal of Information Processing Systems
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• 제14권1호
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• pp.32-55
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• 2018

The digitization of music has seen a considerable increase in audience size from a few localized listeners to a wider range of global listeners. At the same time, the digitization brings the challenge of smoothly retrieving music from large databases. To deal with this challenge, many systems which support the smooth retrieval of musical data have been developed. At the computational level, a query music piece is compared with the rest of the music pieces in the database. These systems, music information retrieval (MIR systems), work for various applications such as general music retrieval, plagiarism detection, music recommendation, and musicology. This paper mainly addresses two parts of the MIR research area. First, it presents a general overview of MIR, which will examine the history of MIR, the functionality of MIR, application areas of MIR, and the components of MIR. Second, we will investigate music similarity measurement methods, where we provide a comparative analysis of state of the art methods. The scope of this paper focuses on comparative analysis of the accuracy and efficiency of a few key MIR systems. These analyses help in understanding the current and future challenges associated with the field of MIR systems and music similarity measures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권5호
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• pp.548-574
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• 2009

Personal information (hereinafter referred to as "PI") infringement has recently emerged as a serious social problem in Korea. PI infringement in the public and private sector is common. There were 182,666 cases of PI in 2,624 public organizations during the last three years. Online infringement cases have increased. PI leakage causes moral and economic damage and is an impediment to public confidence in public organizations seeking to manage e-government and maintain open and aboveboard administration. Thus, it is an important matter. Most cases of PI leakage result from unsatisfactory management of security, errors in home page design and insufficient system protection management. Protection management, such as encryption or management of access logs should be reinforced urgently. However, it is difficult to comprehend the scope of practical technology management satisfied legislation and regulations. Substantial protective countermeasures, such as access control, certification, log management and encryption need to be established. It is hard to deal with the massive leakage of PI and its security management. Therefore, in this study, we analyzed the conditions for the technical protection measures during the processing phase of PI. In addition, we classified the standard control items of protective measures suited to public circumstances. Therefore, this study provides a standard and checklist by which staff in public organizations can protect PI via technical management activities appropriate to laws and ordinances. In addition, this can lead to more detailed and clearer instructions on how to carry out technical protection measures and to evaluate the current status.

• 한국신뢰성학회지:신뢰성응용연구
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• 제18권3호
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• pp.208-212
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• 2018

Purpose: The three Vs of volume, velocity and variety are commonly used to characterize different aspects of Big Data. Volume refers to the amount of data, variety refers to the number of types of data and velocity refers to the speed of data processing. According to these characteristics, the size of Big Data varies rapidly, some data buckets will contain outliers, and buckets might have different sizes. Correlation plays a big role in Big Data. We need something better than usual correlation measures. Methods: The correlation measures offered by traditional statistics are compared. And conditions to meet the characteristics of Big Data are suggested. Finally the correlation measure that satisfies the suggested conditions is recommended. Results: Mutual Information satisfies the suggested conditions. Conclusion: This article builds on traditional correlation measures to analyze the co-relation between two variables. The conditions for correlation measures to meet the characteristics of Big Data are suggested. The correlation measure that satisfies these conditions is recommended. It is Mutual Information.