• Journal of Korean Elementary Science Education
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• v.35 no.3
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• pp.377-387
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• 2016

Whether textbooks faithfully reflect the curriculum contents is an important educational issue. The previous studies on the textbooks did not analyze the relationship described in the textbooks or the structure. In this regard, this study aims to analyze how the concept of life science area in the elementary school science textbooks developed on the basis of the 2009 revised curriculum is linked. In addition, it seeks to analyze how the concept presented in the learning content achievement standards of the curriculum is connected to other concepts. Towards this end, the conceptual linkage of eight units in the life science domain of elementary school science textbooks based on the 2009 revised curriculum was analyzed. The contents of the life science domain in the science textbooks were analyzed through a semantic network analysis, and the semantic network on the concept linked to the one described in curriculum's learning objectives was also analyzed. The results are as follows: 1) It will be difficult for students to understand the concept due to the complexity of the semantic network resulting from a number of concepts. 2) The curriculum's learning objectives presented in the curriculum are not faithfully reflected in the textbooks. 3) The textbooks are described on the basis of specific curriculum's learning objectives. Based on the findings of this study, the number of concepts described in the elementary school science textbooks needs to be significantly reduced so that the concepts can be meaningfully linked to each other.

• Journal of the Korean earth science society
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• v.34 no.2
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• pp.148-161
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• 2013

The purpose of the study was to investigate the relationship between the communication status in group and the semantic network of science gifted students. Seven small groups, 5 members in each, participated in small group activities, in which they discussed the calculation of earth density. Both the communication status in group and the semantic network of science gifted students were analyzed using KrKwic, Ucinet 6.0 for Windows. As a result, the semantic network of prime movers in group represented more frequently used words, lesser rate of component, and higher density than that of out lookers. It means that the prime movers have coherent knowledge compared to out lookers, and they output more knowledge for problem solving than out lookers. Therefore, the results of this study may be applied to evaluating the cognitive level of science gifted students and group organization for small group activity.

• Journal of Korean Academy of Nursing
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• v.47 no.6
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• pp.806-816
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• 2017

Purpose: As comprehensive nursing care service has gradually expanded, it has become necessary to explore the various opinions about it. The purpose of this study is to explore the large amount of text data regarding comprehensive nursing care service extracted from online news and social media by applying a semantic network analysis. Methods: The web pages of the Korean Nurses Association (KNA) News, major daily newspapers, and Twitter were crawled by searching the keyword 'comprehensive nursing care service' using Python. A morphological analysis was performed using KoNLPy. Nodes on a 'comprehensive nursing care service' cluster were selected, and frequency, edge weight, and degree centrality were calculated and visualized with Gephi for the semantic network. Results: A total of 536 news pages and 464 tweets were analyzed. In the KNA News and major daily newspapers, 'nursing workforce' and 'nursing service' were highly rated in frequency, edge weight, and degree centrality. On Twitter, the most frequent nodes were 'National Health Insurance Service' and 'comprehensive nursing care service hospital.' The nodes with the highest edge weight were 'national health insurance,' 'wards without caregiver presence,' and 'caregiving costs.' 'National Health Insurance Service' was highest in degree centrality. Conclusion: This study provides an example of how to use atypical big data for a nursing issue through semantic network analysis to explore diverse perspectives surrounding the nursing community through various media sources. Applying semantic network analysis to online big data to gather information regarding various nursing issues would help to explore opinions for formulating and implementing nursing policies.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.19-29
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• 2016

This paper suggests a method to refine a massive collective intelligence data, and visualize with multilevel sentiment network, in order to understand information in an intuitive and semantic way. For this study, we first calculated a frequency of sentiment words from each movie review. Second, we designed a Heatmap visualization to effectively discover the main emotions on each online movie review. Third, we formed a Sentiment-Movie Network combining the MDS Map and Social Network in order to fix the movie network topology, while creating a network graph to enable the clustering of similar nodes. Finally, we evaluated our progress to verify if it is actually helpful to improve user cognition for multilevel analysis experience compared to the existing network system, thus concluded that our method provides improved user experience in terms of cognition, being appropriate as an alternative method for semantic understanding.

• Journal of Korean Library and Information Science Society
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• v.47 no.3
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• pp.95-114
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• 2016

The purpose of this preliminary study is to collect specific examples of book reports and understand semantic characteristics of them through semantic network. The analysis was conducted with 23 book reports which classified by three groups. The keywords were selected from the of book reports. Five types of keyword network were composed based on co-occurrence relations with keywords. The result of this study is following these. First, each keyword network of book reports of groups and individuals is shown to have different structural characteristics. Second, each network has different high centrality keywords according to the result analysis of 3 types of centrality(degree centrality, closeness centrality, betweenness centrality). These characteristic means that keyword network analysis is useful in recognizing the characteristics of not only groups' and but also individual's book reports.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.6
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• pp.727-731
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• 2010

Recently, mobile life-log data are collected by mobile devices and used to recode one's life. In order to help a user search data, a mobile life-log semantic network is introduced for storing logs and retrieving associative information. However, associative search systems on common semantic networks in previous studies provide for a user with only found data as text to users. This paper proposes an associative search system for mobile life-log semantic network that supports selection and keyword associative search of which a process and result are a visualized graph representing associative data and their relationships when a user inputs a keyword for search. In addition, by using semantic abstraction, the system improves user's understanding of search result and simplifies the resulting graph. The system's usability was tested by an experiment comparing the system and a text-based search system.

• Journal of KIISE:Databases
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• v.28 no.2
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• pp.188-203
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• 2001

멀티데이터베이스 시스템(multidatabase system)에서 여러 요소 데이터베이스(component database)에 대한 통합된 접근을 제공하기 위해서는 의미 이질성(semantic heterogeneity)이 탐색되고 해결되어져야 한다. 즉, 멀티데이터베이스 시스템은 각 요소 데이터베이스가 가지고 있는 정보의 의미를 이해하고 의미적으로 동등한 또는 유사한 정보들을 식별할 수 있어야 한다. 또한, 멀티데이터베이스 시스템은 사용자로 하여금 실세계의 동일한 정보를 가지고 있는 여러 다른 데이터베이스로부터 원하는 정보를 용이하게 획득할 수 있도록 해야 한다. 본 논문에서는, 요소 데이터베이스간의 의미 이질성을 탐색하고 해결하기 위하여 정보가 갖고 있는 개념간 의미관계에 기반한 의미망(semantic network)을 구축한다. 또한 의미질의어(semantic query language)를 제공하여 사용자가 스키마에 대한 사전 지식이 없이도 여로 자율적인 데이터베이스로부터 원하는 정보를 용이하게 획득 할 수 있도록 한다.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.87-97
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• 2023

Unmanned aerial vehicles (UAVs) can capture high-resolution imagery from a variety of viewing angles and altitudes; they are generally limited to collecting images of small scenes from larger regions. To improve the utility of UAV-appropriated datasetsfor use with deep learning applications, multiple datasets created from variousregions under different conditions are needed. To demonstrate a powerful new method for integrating heterogeneous UAV datasets, this paper applies a combined segmentation network (CSN) to share UAVid and semantic drone dataset encoding blocks to learn their general features, whereas its decoding blocks are trained separately on each dataset. Experimental results show that our CSN improves the accuracy of specific classes (e.g., cars), which currently comprise a low ratio in both datasets. From this result, it is expected that the range of UAV dataset utilization will increase.

• The Journal of Korean Association of Computer Education
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• v.3 no.1
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• pp.177-189
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• 2000

This paper describes the design and implementation of Korean History Web courseware using semantic network in order to build learning environment in the viewpoint of cognitive flexibility theory. The most important thing in design for a courseware using semantic network is to build learning environment. The first step to do this is to analyze learning contents and after that we should define the type of link between learning subjects. We should develope the knowledge map which has the link of each type connected with every learning subject.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2003.06a
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• pp.57-59
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• 2003