• Journal of KIISE:Software and Applications
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• v.35 no.10
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• pp.627-635
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• 2008

An extended form of lexical network is explored by presenting U-WIN, which applies lexical relations that include not only semantic relations but also conceptual relations, morphological relations and syntactic relations, in a way different with existing lexical networks that have been centered around linking structures with semantic relations. So, This study introduces the new methodology for constructing a syntactic relation automatically. First of all, we extract probable nouns which related to verb based on verb's sentence type. However we should decided the extracted noun's meaning because extracted noun has many meanings. So in this study, we propose that noun's meaning is decided by the example matching rule/syntactic pattern/semantic similarity, frequency information. In addition, syntactic pattern is expanded using nouns which have high frequency in corpora.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.371-382
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• 2017

This study aims to analyze the research trend of cultural policy-related papers based on 832 key words among 186 whole articles in the Journal of Cultural Policy by the Korea Culture & Tourism Institute from October 2008 to January 2017. The analysis was performed using a big data analysis technique called the Semantic Network Analysis. The Semantic Network Analysis consists of frequency analysis, density analysis, centrality analysis including degree centrality, betweenness centrality, and eigenvector centrality. Lastly, the study shows a figure visualizing the results of the centrality analysis through Netdraw program. The most frequently exposed key words were 'culture', 'cultural policy/administration', 'cultural industry/cultural content', 'policy', 'creative industry', in the order. The key word 'culture' was ranked as the first in all the analysis of degree centrality, betweenness centrality and eigenvector centrality, followed by 'policy' and 'cultural policy/administraion'. The key word 'cultural industry/cultural content' with very high frequency recorded high points in degree centrality and eigenvector centrality, but showed relatively low points in betweenness centrality.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.213-216
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• 2018

As the advantages of smart devices based on artificial intelligence and voice recognition become more prominent, Virtual Assistant is gaining popularity. Virtual Assistant provides a user experience through smart speakers and is valued as the most user friendly IoT device by consumers. The purpose of this study is to investigate whether there are differences in people's perception of the key virtual assistant brand voice recognition. We collected tweets that included six keyword form three companies that provide Virtual Assistant services. The authors conducted semantic network analysis for the collected datasets and analyzed the feelings of people through sentiment analysis. The result shows that many people have a different perception and mainly about the functions and services provided by the Virtual Assistant and the expectation and usability of the services. Also, people responded positively to most keywords.

• Journal of recreation and landscape
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• v.12 no.4
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• pp.45-58
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• 2018

Place memory is a new way of seeing as a new concept of cultural landscape research. Various research works and discussions have recently spread in landscape studies. In particular, the, which is visible and material, is a medium in which collective memory is embedded in place memory. The purpose of this study is to extract places of memory from the collective memory of residents of Janghang, Korea, and to visualize it through semantic relations. For this purpose, semi-standardized interviews (34 persons) were conducted with residents, and frequency analysis and semantic network analysis were used. As a result, the interviewees recalled only 127 places in Janghang that existed between 1920 and 2010. Locals remember the city based on places of memory. This means that the city could be illustrated according to specific places that are frequently mentioned. For instance, the top 25 places (top 20%) explain 65.6% of all the places in the city, and the top 39 places (top 30.8%) could describe 78.7% of the places. Some places are referred to more frequently when they are in the city's symbolic landscape, and the city's identity is projected on them. Some places were mentioned only infrequently but were nevertheless very important places by which to understand Janghang. These places of memory have not appeared in the documentary records before, which shows the value of the collective memory of the locals and the effectiveness of the interviewing method. In the clustering of the semantic network, six groups of places appeared. The local residents remembered the modern industrial city and recalled it in connection with the sites of daily life. This shows the possibility of looking not only at public memory and famous heritage as a macro history but also at daily life and meaningful places as a micro history about locals. This study has significance as an initial research that identified and visualized places of memory from the perspective of local residents. Such an approach could be useful in the study of everyday life and the conservation of modern heritage.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.1-6
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• 2019

This study visualized users reaction about movies based on keywords with high frequency. For this work, we collected data of movie reviews on . A total of six movies were selected, and we conducted the work of data gathering and preprocessing. Semantic network analysis was used to understand the relationship among keywords. Also, NetDraw, packaged with UCINET, was used for data visualization. In this study, we identified the differences in characteristics of review contents regarding each movie. The implication of this study is that we visualized movie reviews made by sentence as keywords and explored whether it is possible to construct the interface to check users' reaction at a glance. We suggest that further studies use more diverse movie reviews, and the number of reviews for each movie is used in similar quantities for research.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.30 no.1
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• pp.181-207
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• 2019

This study analyzed social issues related to presidential records in press releases using semantic network analysis method. For this purpose, we 1) selected five major news medias in Korea - Chosun Ilbo, JoongAng Ilbo, Dong-A Ilbo, Hankyoreh, and Kyunghyang Newspaper; 2) collected relevant articles including the subject word "Presidential Records", and 3) analyzed issue trends based on timeline using semantic network. According to medias, the issue related to the presidential records were analyzed by comparing the specific keywords in terms of persons, entities, actions. At the results, It is possible to identify the reporting patterns and components of the presidential records related issues. And the difference of media characteristics according to news media tendency was derived.

• 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.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.967-978
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• 2023

This study proposed and validated a combined segmentation network (CSN) designed to effectively train on multiple drone image datasets and enhance the accuracy of semantic segmentation. CSN shares the entire encoding domain to accommodate the diversity of three drone datasets, while the decoding domains are trained independently. During training, the segmentation accuracy of CSN was lower compared to U-Net and the pyramid scene parsing network (PSPNet) on single datasets because it considers loss values for all dataset simultaneously. However, when applied to domestic autonomous drone images, CSN demonstrated the ability to classify pixels into appropriate classes without requiring additional training, outperforming PSPNet. This research suggests that CSN can serve as a valuable tool for effectively training on diverse drone image datasets and improving object recognition accuracy in new regions.

• Journal of Information Processing Systems
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• v.6 no.3
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• pp.359-374
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• 2010

The Future Internet that includes Real World Objects and the Internet of Things together with the more classic web pages will move communications from a nodecentric organization to an information-centric network allowing new a paradigm to take place. The 4WARD project initiated some works on the Future Internet. One of them is the creation of a Network of Information designed to enable more powerful semantic searches. In this paper, we propose a security solution for a model of information based on a semantic description and search of objects. The proposed solution takes into account both the access and the management of both objects and their descriptions.

• Proceedings of the IEEK Conference
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• summer
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• pp.159-164
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• 2004

This paper aims towards designing and implementation of a new adaptive Peer to Peer (P2P) network that cluster itself on the basis of semantic proximity. We also developed an algorithm to classify the nodes to form the semantic groups and to direct the queries to appropriate groups without any human intervention. This is done using Bloom filters to summarise keywords of the documents shared by a peer. The queries are directed towards the appropriate clusters instead of flooding them. The proposed topology supports a system for maintaining a global, omnipresent trust value for each peer in an efficient manner both in terms of decision time and network load.