• Spatial Information Research
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• v.19 no.4
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• pp.91-97
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• 2011

In this paper, we propose an architecture for geosemantic services. With the rapid progress of web services, wireless internet technologies and popularization of smart phone in recent years, a lot of applications based on geographic information are being developed. Moreover the search portals empowered by semantic web technologies are enabling general users to access on-line resources more easily. However, several studies in GIS domain have pointed out the practical limitation of existing service patterns, which are limited only to linking heterogenous spatial databases, insufficient for several important use cases. Hence we draw functional elements of geosemantic services from GIS and semantic web standards, and present the use cases and a new architecture for geosemantic services. This approach could set a foundation to implement geoemantic services.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.71-79
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• 2007

Recent advances in the internet infrastructure have resulted in a large number of huge Web sites and portals worldwide. These Web sites are being visited by various types of users in many different ways. Among all the web page access sequences from different users, some of them occur so frequently that may need an attention from those who are interested. We call them frequent access patterns and access sequences that can be frequent the candidate patterns. Since these candidate patterns play an important role in the incremental Web mining, it is important to efficiently generate, add, delete, and search for them. This thesis presents a novel tree structure that can efficiently store the candidate patterns and a related set of algorithms for generating the tree structure, adding new patterns, deleting unnecessary patterns, and searching for the needed ones. The proposed tree structure has a kind of the 3 dimensional link structure and its nodes are layered.

• Journal of Information Management
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• v.36 no.4
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• pp.71-89
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• 2005

This paper examines the ways of using information resources available through information retrieval systems of portal sites. We analyze the types of information resources, search capabilities, and interfaces of Naver, Empas, and Google Scholar. Naver's retrieval system sells research reports, papers, patents information, etc. to users, which is similar to C2C(Customer to Customer in e-commerce environment). Empas provides information from journals, research reports, and proceedings with no charge. Google Scholar's noteworthy efforts are their collaborative programs with and/or for major U.S. libraries, such as "Library Link" and "Library Project." Considering the extended information retrieval services of portals, especially the services like Google Scholar's library programs, libraries need to develop more specialized services, such as the customized information service for individual user, development of user convenience tools like OCLC WorldCat, more accessibility through ubiquitous library concept, and collaboration among libraries.

• Fashion & Textile Research Journal
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• v.16 no.2
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• pp.208-217
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• 2014

This study focuses on analyzing a subset of consumer activities (especially social medium) in their wedding preparation. The focus of this study is on wedding online communities and understanding the impact of communities on selective behavior for information-acceptance. Data was compiled based on female consumers in their 20s and 30s who actively participate in online community forums. It included female consumers preparing for their weddings and individuals interested in weddings. A total of 211 questionnaires were collected from January $10^{th}$ to $23^{rd}$ in 2012. The online communities were identified from Naver, Yahoo, and online search portals; subsequently, they were rank-sorted based on number of members, visitors, and forum posts. We identified four different characteristic based on the findings from the analysis of on-line wedding communities. The characteristic of these communities were divided into sharing experience, functionality of the webpage, informativeness, and interactivity; consequently, use of these online communities is based on trust and significant personal relationships between the members online. Out of the four different community characteristics, sharing experience was found to have a greater impact for the selective behavior of wedding dresses and information- acceptance than the functionality of the webpage, interactivity, and informativeness. We conclude that trust in information provided by members with marriage process experience is the foremost important factor in the behavior of individual consumers wit iexplore.exe -extoff hout marriage process experience. Therefore, the impact of these online communities catering to would-be brides is based on the trust of posters and how well it is articulated.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.305-313
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• 2018

Public open data is a database or electronic file produced by a public agency or government. The government is opening public data through the open data portals and individual agency websites. However, it is a reality that there is a limit to search and utilize desired public data from the perspective of data users. In particular, it takes a great deal of effort and time to understand the characteristics of data sets and to combine different data sets. This study suggests the possibility of interlinking between data sets by analyzing the common relationship of item names held by public data. The data sets are collected from the open data portal, and item names included in the data sets are extracted. The extracted item names consist of formal context and formal concept through formal concept analysis. The format concept has a list of data sets and a set of item name as extent and intent, respectively, and analyzes the common items of intent end to determine the possibility of data connection. The results derived from the formal concept analysis can be effectively applied to the semantic connection of the public data, and can be applied to data standard and quality improvement for public data release.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.999-1005
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• 2020

While search portals' 'Portal News' account for the largest portion of aggregated news outlet, its neutrality as an outlet is questionable. This is because news aggregation may lead to prejudiced information consumption by recommending biased news articles. In this paper we introduce a new method of measuring political bias of news articles by using deep learning. It can provide its readers with insights on critical thinking. For this method, we build the dataset for deep learning by analyzing articles' bias from keywords, sourced from the National Assembly proceedings, and assigning bias to said keywords. Based on these data, news article bias is calculated by applying deep learning with a combination of Convolution Neural Network and Recurrent Neural Network. Using this method, 95.6% of sentences are correctly distinguished as either conservative or progressive-biased; on the entire article, the accuracy is 46.0%. This enables analyzing any articles' bias between conservative and progressive unlike previous methods that were limited on article subjects.

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.439-448
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• 2022

This study aims to search for education-related datasets provided by public data portals and examine what data types are constructed through classification using topic modeling methods. Regarding the data of the public data portal, 3,072 cases of file data in the education field were collected based on the classification system. Text mining analysis was performed using the LDA-based topic modeling method with stopword processing and data pre-processing for each dataset. Program information and student-supporting notifications were usually provided in the pre-classified dataset for education from the data portal. On the other hand, the characteristics of educational programs and supporting information for the disabled, parents, the elderly, and children through the perspective of lifelong education were generally indicated in the dataset collected by searching for education. The results of data analysis through this study show that providing sufficient educational information through the public data portal would be better to help the students' data science-based decision-making and problem-solving skills.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.655-661
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• 2023

Big data, an important element of the 4th industrial revolution, is actively opening public data in public institutions and local governments. In the public data portal, everyone can conveniently search for data and check related data, but only those in ICT-related fields are using public data. Although data held by public institutions is open to citizens, it is difficult for anyone to easily utilize public data to develop applications. In this paper, data provided in open API format from public data portals has XML and JSON formats. In this study, we are a method of modularizing public data in XML format into a part that can be easily developed by linking it to a GUI interface. Based on the necessary public data, we propose a way to easily develop mobile programs and promote the use of public data.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.519-528
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• 2023

Recently, for the preservation and transmission of cultural heritage, various researches and content development based on technologies such as virtual reality, augmented reality, and extended reality, which are the core technologies of the 4th industrial revolution era, are being conducted. Intangible cultural heritage is variable, unlike tangible cultural heritage, so it changes greatly depending on time and space, and as a result, it is in danger of being discontinued due to the aging and death of the inheritors. In this study, the current status and cases of related realistic content production were collected and analyzed, focusing on statistical data, intangible cultural heritage training centers through search portals, and platform cases. As a result of the analysis, it was found that overall, there were very few cases of use in content and transfer education using intangible cultural heritage. Through this study, we will consider ways to revitalize the effective transfer education of intangible cultural heritage that is on the verge of being cut off from transmission.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.1
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• pp.76-81
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• 2018

The Internet of Things (IoT), which is emerging as a future economic growth engine, has been actively introduced in areas close to our daily lives. However, there are still IoT security threats that need to be resolved. In particular, with the spread of smart homes and smart cities, an explosive amount of closed-circuit televisions (CCTVs) have been installed. The Internet protocol (IP) information and even port numbers assigned to CCTVs are open to the public via search engines of web portals or on social media platforms, such as Facebook and Twitter; even with simple tools these pieces of information can be easily hacked. For this reason, a big-data analytics system is needed, capable of supporting quick responses against data, that can potentially contain risk factors to security or illegal websites that may cause social problems, by assisting in analyzing data collected by search engines and social media platforms, frequently utilized by Internet users, as well as data on illegal websites.