• IEIE Transactions on Smart Processing and Computing
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• v.5 no.3
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• pp.222-229
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• 2016

Linked Data is a powerful technology for storing and publishing the structures of data. It is helpful for web applications because of its usefulness through semantic query data. However, using Linked Data is not easy for ordinary users who lack knowledge about the structure of data or the query syntax of Linked Data. For that problem, we propose a translator component that is used for translating RESTful/JSON request messages into SPARQL commands based on ontology - a metadata that describes the structure of data. Clients do not need to worry about the structure of stored data or SPARQL, a kind of query language used for querying linked data that not many people know, when they insert a new instance or query for all instances of any specific class with those complex structure data. In addition, the translator component has the search function that can find a set of data from multiple classes based on finding the shortest paths between the target classes - the original set that user provide, and target classes- the users want to get. This translator component will be applied for any dynamic ontological structure as well as automatically generate a SPARQL command based on users' request message.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3419-3437
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• 2022

Anonymization technology is an important technology for privacy protection in the process of data release. Usually, before publishing data, the data publisher needs to use anonymization technology to anonymize the original data, and then publish the anonymized data. However, for data publishers who do not have or have less anonymized technical knowledge background, how to configure appropriate parameters for data with different characteristics has become a more difficult problem. In response to this problem, this paper adds a historical configuration scheme resource pool on the basis of the traditional anonymization process, and configuration parameters can be automatically recommended through the historical configuration scheme resource pool. On this basis, a privacy model hybrid recommendation algorithm for user satisfaction is formed. The algorithm includes a forward recommendation process and a reverse recommendation process, which can respectively perform data anonymization processing for users with different anonymization technical knowledge backgrounds. The privacy model hybrid recommendation algorithm for user satisfaction described in this paper is suitable for a wider population, providing a simpler, more efficient and automated solution for data anonymization, reducing data processing time and improving the quality of anonymized data, which enhances data protection capabilities.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.17-24
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• 2018

Today, we are living in the era of data and information. With the advent of Internet of Things (IoT), the popularity of social networking sites, and the development of mobile devices, a large amount of data is being produced in diverse areas. The collection of such data generated in various area is called big data. As the importance of big data grows, there has been a growing need to share big data containing information regarding an individual entity. As big data contains sensitive information about individuals, directly releasing it for public use may violate existing privacy requirements. Thus, privacy-preserving data publishing (PPDP) has been actively studied to share big data containing personal information for public use, while preserving the privacy of the individual. K-anonymity, which is the most popular method in the area of PPDP, transforms each record in a table such that at least k records have the same values for the given quasi-identifier attributes, and thus each record is indistinguishable from other records in the same class. As the size of big data continuously getting larger, there is a growing demand for the method which can efficiently anonymize vast amount of dta. Thus, in this paper, we develop an efficient k-anonymity method by using Spark distributed framework. Experimental results show that, through the developed method, significant gains in processing time can be achieved.

• Biomedical Science Letters
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• v.10 no.4
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• pp.485-493
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• 2004

In the current field of Medical Informatics, the information increases, and changes fast, so we can access the various data types which are ranged from text to image type. A small number of technician digitizes these data to establish database, but it is needed a lot of money and time. Therefore digitization by many end-users confronting data and establishment of searching database is needed to manage increasing information effectively. New data and information are taken fast to provide the quality of care, diagnosis which is the basic work in the medicine. And also It is needed the medical database for purpose of private study and novice education, which is tool to make various data become knowledge. However, current medical database is used and developed only for the purpose of hospital work management. In this study, using text input, file import and object images are digitized to establish database by people who are worked at the medicine field but can not expertise to program. Data are hierarchically constructed and then knowledge is established using a tree type database establishment method. Consequently, we can get data fast and exactly through search, apply it to study as subject-oriented classification, apply it to diagnosis as time-depended reflection of data, and apply it to education and precaution through function of publishing questions and reusability of data.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.177-193
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• 2014

Over the past decade, there has been a rapid diffusion of electronic commerce and a rising number of interconnected networks, resulting in an escalation of security threats and privacy concerns. Electronic commerce has a built-in trade-off between the necessity of providing at least some personal information to consummate an online transaction, and the risk of negative consequences from providing such information. More recently, the frequent disclosure of private information has raised concerns about privacy and its impacts. This has motivated researchers in various fields to explore information privacy issues to address these concerns. Accordingly, the necessity for information privacy policies and technologies for collecting and storing data, and information privacy research in various fields such as medicine, computer science, business, and statistics has increased. The occurrence of various information security accidents have made finding experts in the information security field an important issue. Objective measures for finding such experts are required, as it is currently rather subjective. Based on social network analysis, this paper focused on a framework to evaluate the process of finding experts in the information security field. We collected data from the National Discovery for Science Leaders (NDSL) database, initially collecting about 2000 papers covering the period between 2005 and 2013. Outliers and the data of irrelevant papers were dropped, leaving 784 papers to test the suggested hypotheses. The co-authorship network data for co-author relationship, publisher, affiliation, and so on were analyzed using social network measures including centrality and structural hole. The results of our model estimation are as follows. With the exception of Hypothesis 3, which deals with the relationship between eigenvector centrality and performance, all of our hypotheses were supported. In line with our hypothesis, degree centrality (H1) was supported with its positive influence on the researchers' publishing performance (p<0.001). This finding indicates that as the degree of cooperation increased, the more the publishing performance of researchers increased. In addition, closeness centrality (H2) was also positively associated with researchers' publishing performance (p<0.001), suggesting that, as the efficiency of information acquisition increased, the more the researchers' publishing performance increased. This paper identified the difference in publishing performance among researchers. The analysis can be used to identify core experts and evaluate their performance in the information privacy research field. The co-authorship network for information privacy can aid in understanding the deep relationships among researchers. In addition, extracting characteristics of publishers and affiliations, this paper suggested an understanding of the social network measures and their potential for finding experts in the information privacy field. Social concerns about securing the objectivity of experts have increased, because experts in the information privacy field frequently participate in political consultation, and business education support and evaluation. In terms of practical implications, this research suggests an objective framework for experts in the information privacy field, and is useful for people who are in charge of managing research human resources. This study has some limitations, providing opportunities and suggestions for future research. Presenting the difference in information diffusion according to media and proximity presents difficulties for the generalization of the theory due to the small sample size. Therefore, further studies could consider an increased sample size and media diversity, the difference in information diffusion according to the media type, and information proximity could be explored in more detail. Moreover, previous network research has commonly observed a causal relationship between the independent and dependent variable (Kadushin, 2012). In this study, degree centrality as an independent variable might have causal relationship with performance as a dependent variable. However, in the case of network analysis research, network indices could be computed after the network relationship is created. An annual analysis could help mitigate this limitation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.405-424
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• 2013

In publishing applications, it is advantageous to embed data in halftone images. The CPT scheme (Chen-Pan-Tseng, 2000) is a steganographic data hiding scheme that was proposed for binary images, e.g., facsimiles. The CPT scheme uses a secret key and weight matrix to protect the hidden data and can hide as many as $r={\lfloor}{\log}_2(m{\times}n+1){\rfloor}$ bits of data in the image by changing at most 2 bits in the image. Our proposed scheme also uses a secret key to protect it from being compromised and a weight matrix to increase the data hiding rate. Our scheme improves the performance of the CPT scheme by using the simple principle of splitting each block into two parts. Our proposed scheme is called improved CPT (ICPT) and has a very high embedding capacity compared to previous schemes. Experimental results demonstrate that our proposed scheme generally has higher performance than previous schemes.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.9
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• pp.712-718
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• 1991

In this paper, we propose a graphic system for high speed generation of bitmap font data from the outline font data such as PostScript, etc. In desk-top publishing system. A VLSI chip called KAFOG was designed for the high-speed calculation of a cubic Bezier curve, which was implemented in 1.5\ulcorner CMOS gate array using 17,000 gates. A cubic Bezier curve is approximated by a set of line segments in KAFOG at the throughput of 250K curves per second with the clock frequency of 40 MHz. A prototype graphic system was developed using two MC6800 microprocessors and the KAFOG chip. Two microprocessors cooperate in a master and slave mode, and handshaking is used for communication between two processors. KAFOG chip, being controlled by the slave processor, operates as a coprocessor for the calculation of the outline font. The throughput of the prototype graphic system is 40 64$\times$64 outline fonts per sencond.

• Language and Information
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• v.6 no.2
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• pp.33-55
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• 2002

This research aims at transforming the definition tort of an English-English-Korean Dictionary (EEKD) which is encoded in EST files for the purpose of publishing into a structured format for Lexical Data Base (LDB). The construction of LDB is very time-consuming and expensive work. In order to save time and efforts in building new lexical information, the present study tries to extract useful linguistic information from an existing printed dictionary. In this paper, the process of extraction and structuring of lexical information from a printed dictionary (EEKD) as a lexical resource is described. The extracted information is represented in XML format, which can be transformed into another representation for different application requirements.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.344-348
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• 2021

The article examines one of the most important means of visualization of mass information on the Internet - information graphics in the broadest sense of the term as a visual technology for presenting mass information. The main objectives of the article are to determine the genre-typological features of infographics and basic technological principles; identification of features of creation and use of information graphics in modern network. Certain benefits of online infographic editors include savings in resources and time. They allow the user, who has basic PC skills, to create standardized infographics based on their own data. In addition, the use of online services develops visual thinking, allows you to get an idea of quality criteria and current trends in infographics, as well as to gain initial experience in the visual presentation of data.

• Journal of Korea Technology Innovation Society
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• v.11 no.4
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• pp.510-531
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• 2008

The importance of universities' knowledge to industrial innovation have widely pervaded the academia as well as policy communities. During the last three decades, a series of policy measures vitalizing the knowledge-transfer activities of academics have been implemented both in industrialized and industrializing countries. However, The concerns on the industry's influences on the academia have been raised by a group of researchers such as 'Economics of science'. Against this background, this paper addresses the issues related to the relationship between the academic research and knowledge-transfer activities. Particularly, based on the 16 years' panel data of Korean academics' patent and paper outputs, the effect of patenting activities on publishing activities is investigated. Moreover, the specific context of Korean academic system as well as general characteristics of academics are considered in the analysis and discussion. According to the results, not just the publishing and patenting outputs but their productivities have been dramatically increased during the last 16 years. The main finding is that the patenting activities have a consistent positive effect on the publishing activities of the academics in the estimations of panel models. Based on these results and the discussions, some policy recommendations for university-industry collaboration are suggested.