• Journal of Korean Society of Archives and Records Management
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• v.15 no.2
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• pp.55-82
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• 2015

The Presidential Archives preserve and manage the president's records and archives, which accounts for the social and governmental operations during the president's term of office. However, search systems and online contents provided by the Presidential Archives are difficult to use. This study proposed an LOD-based archival information service for the comfort of users. The proposed service has a better extension of archival information service contents from President Roh's term. The provision of details is divided into three steps: first step sets up the establishment methods, second step creates ontological design, and third step converts it to RDF and connects to other institutions. Through the process, this study suggests an extension of archival information service in the Presidential Archives.

• Journal of Intelligence and Information Systems
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• v.11 no.1
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• pp.153-167
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• 2005

In this paper, we consider the problem of exploring unknown environments with a mobile robot or an autonomous character agent. Traditionally, research efforts to address the space exploration problem havefocused on the graph-based space representations and the graph search algorithms. Recently EXPLORE, one of the most efficient search algorithms, has been discovered. It traverses at most min$min(mn, d^2+m)$ edges where d is the deficiency of a edges and n is the number of edges and n is the number of vertices. In this paper, we propose DFS-RTA* and DFS-PHA*, two real-time graph search algorithms for directing an autonomous agent to explore in an unknown space. These algorithms are all built upon the simple depth-first search (DFS) like EXPLORE. However, they adopt different real-time shortest path-finding methods for fast backtracking to the latest node, RTA* and PHA*, respectively. Through some experiments using Unreal Tournament, a 3D online game environment, and KGBot, an intelligent character agent, we analyze completeness and efficiency of two algorithms.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.653-668
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• 2012

In this study, an improved HMM based recognition model is proposed for online English and Korean handwritten characters. The pattern elements of the handwriting model are sub character strokes and ligatures. To deal with the problem of handwriting style variations, a modified Hierarchical Clustering approach is introduced to partition different writing styles into several classes. For each of the English letters and each primitive grapheme in Korean characters, one HMM that models the temporal and spatial variability of the handwriting is constructed based on each class. Then the HMMs of Korean graphemes are concatenated to form the Korean character models. The recognition of handwritten characters is implemented by a modified level building algorithm, which incorporates the Korean character combination rules within the efficient network search procedure. Due to the limitation of the HMM based method, a post-processing procedure that takes the global and structural features into account is proposed. Experiments showed that the proposed recognition system achieved a high writer independent recognition rate on unconstrained samples of both English and Korean characters. The comparison with other schemes of HMM-based recognition was also performed to evaluate the system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3960-3975
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• 2022

To analyze and compare the most influencing factors on cloud computing adoption (CCA) in the healthcare organization, a systematic review and meta-analyses of studies was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Cochrane collaboration recommendations. A search of PubMed, ScienceDirect, Springer, Wiley Online, and Taylor & Francis Online digital libraries (From inception to January 19, 2022) was performed. A total of 17 studies met the defined studies' inclusion and exclusion criteria. Statistical significance difference favoring most influencing factors on CCA were (MD 0.76, 95% CI -1.48 - 3.01, p <0.00001, I² = 90%), (MD 1.40, 95% CI -4.76 - 7.55, p < 0.00007, I² = 97%) (MD 0.17, 95% CI -2.69 - 3.03, p<0.00001, I² = 96%) for technology vs. organizational, technology vs. environmental and business vs. human factors, respectively. Organizational and environmental factors had greater impacts on CCA compared with technological factors. Moreover, business factors were more influential than the human factors.

• 한국노년학
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• v.39 no.1
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• pp.109-125
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• 2019

This study examined factors that prevent older adults from using computers and/or smartphones for their health information search and health management. This study conducted face-to-face survey of a total of 240 older adults aged over 65. Based on the responses of open-ended questions, this study conducted semantic network analysis. The results showed that low level of perceived usefulness(PU) (e.g., information I want to find, detailed information, and trustworthiness) and perceived ease of use(PEOU) (e.g., how to search for information, how to install applications, and visibility) are main factors that prevent older adults from using computers and/or smartphones for their health information search and health management. Furthermore, based on the results of semantic network analysis, further hierarchical regression analysis confirmed that PU and PEOU were positively associated with intention to use mobile application. Thus, the results imply that increasing older adults' PU and PEOU can promote their intention to use mobile application.

• Journal of the East Asian Society of Dietary Life
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• v.27 no.5
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• pp.558-568
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• 2017

This study was conducted to examine the level of exposure, credibility and usefulness of the food tourism information channel perceived by foreign tourists visiting Korea. A total of 230 survey questionnaires were distributed to Japanese and Chinese tourists, who account for the highest percentage of tourists visiting Korea. The results showed that tourists were segmented into three groups based on their participation in food tourism activities: culinary tourists, experiential tourists and general tourists. Japanese tourists participated more actively in food tourism activities than Chinese tourists. The information channel used most frequently by tourists was 'word-of-mouth,' while the least used channel was 'e-mail catalog contains food tourism information.' Culinary tourist most actively used online and offline channels to search for food tourism information. Perceived credibility and usefulness of the food tourism information channel differed by nationality and food tourist segments. This study provides meaningful implications regarding food tourism promotion strategies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.97-99
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• 2014

This study aims to suggest development model for ICT Teaching and Learning System adopting collective intelligence. First, we defined program modules according to functions which multimedia online encyclopedia-type e-textbook should have. Then, we also specified content information creating rules and procedures and content information searching methods. Finally, we developed the prototype which suggests user interface to collect and search information adopting information visualizing techniques. This study has significance in suggesting advanced form of ICT system in which qualified teachers can create, accumulate, and share information and students can explore information and expand search in self-directed manner.

• Journal of Korean Library and Information Science Society
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• v.52 no.3
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• pp.239-266
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• 2021

This study aimed to analyze the usage behaviors of university students seeking and sharing everyday life information through an online community called Everytime. The study was designed based on everyday life information-seeking and activity theory models, and students from various universities were interviewed using a qualitative research method. Findings showed that Everytime users perceive Everytime as a valuable online community for pursuing and sharing everyday life information. It was primarily used to search for university life information, such as academic calendar, class, and graduation, and health, restaurants, and housing. In the case of the freshmen and sophomores who entered during the COVID-19 pandemic, their dependence on Everytime was high, and juniors and seniors who experienced university life before COVID-19 also responded that Everytime is one of the essential sources of information in university life. Although Everytime provides quick and valuable information, users mentioned the moral hazard as a major factor hindering the active use of Everytime. The results of this study are expected to be used as primary data for informatics research on the online community of college students and the development and operation of online communities for university students.

• Journal of Information Management
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• v.24 no.3
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• pp.31-56
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• 1993

In order to respond to the public needs to utilize the newspapers as high-valued information resources, the number of the commercially available news items which are transformed into a form of database has been remarkably increased by the introduction of CTS into the newspaper companies. As for the domestically available Japanese and foreign newspaper article database, explanations are given to the following items. 1) Characteristics of database, such as date of coverage, frequency updating, time-lag, news sources, search terms, available information, etc. 2) Matters to be noticed at the utilization. 3) Pattern of utilization depending on the object of the investigation, such as the investigation of company, market trend, etc. Since the newspaper article database will be available in a form of digitized information, making the combination with the inter-company LAN system possible, increased opportunities to use it in near future are expected.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.2115-2130
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• 2022

With the development of over-the-top (OTT) services, the demand for content is increasing, and you can easily and conveniently acquire various content in the online environment. As a result, copyrighted content can be easily copied and distributed, resulting in serious copyright infringement. Some special forms of online service providers (OSP) use filtering-based technologies to protect copyrights, but illegal uploaders use methods that bypass traditional filters. Uploading with a title that bypasses the filter cannot use a similar search method to detect illegal content. In this paper, we propose a technique for profiling the Heavy Uploader by normalizing the bypassed content title and efficiently detecting illegal content. First, the word is extracted from the normalized title and converted into a bit-array to detect illegal works. This Bloom Filter method has a characteristic that there are false positives but no false negatives. The false positive rate has a trade-off relationship with processing performance. As the false positive rate increases, the processing performance increases, and when the false positive rate decreases, the processing performance increases. We increased the detection rate by directly comparing the word to the result of increasing the false positive rate of the Bloom Filter. The processing time was also as fast as when the false positive rate was increased. Afterwards, we create a function that includes information about overall piracy and identify clustering-based heavy uploaders. Analyze the behavior of heavy uploaders to find the first uploader and detect the source site.