• Journal of the Korean Society of Environmental Restoration Technology
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• v.21 no.3
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• pp.67-81
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• 2018

We tried to analyze qualitatively a total of 110 the research papers which were related domestic ecological restoration technologies about 15 years through semantic network analysis in social network analysis. In order to understand the research trends of ecological restoration technologies, we analyzed the degree centrality and betweenness centrality of the Stream/Wetland, Slope, Soil/Others fields selected as Word Cloud. As a result, ecological restoration technologies have been changed. They were focused on the restoration of species or their habitats in the past. However, they have been evolved into the detailed systems to respond in unpredictable natural disasters and climate change, high-resolution image implementation technology to accurately grasp the practical environment and methods related to environmental restoration for human in urban ecosystem. In the future, investment and technology for the ecosystem restoration field will be continuously demanded for the symbiosis of human beings and species in the damaged ecosystem. Therefore, the research trend of ecological restoration technologies should be provided as reliable guidelines when decision makers establish the policy direction or when researchers select their subjects.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.11a
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• pp.180-184
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• 2005

These days, home network connects all home appliances using one of broadband convergence network, is constructed and propagated to more than 10 million house hold. Users can monitor and control statuses of home appliances using mobile terminal through homeserver. For active propagation of home network, high-quality multimedia service is very important. Specially, as digital recorder and digital camera is propagated, new paradigm that private DVDs can be shared in many household shows up. The homeserver is the main part of UbiHome, which can store much multimedia content and through which the user can search and share these contents. For searching and sharing, the metadata of contents is supposed to keep the consistency. These metadata include the description to different format such as Image, movie, and music. Therefore, we intend to provide a RDF model for effectively storing, searching and managing high-quality contents in UbiHome. In this paper, we propose to make Ontology to close semantic approach using RDF/RDF Schema for managing multimedia data in UbiHome. we propose RDF-Based Local Ontology and merging these ontology to RDF-Based Global Ontology.

• Journal of Contemporary Eastern Asia
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• v.18 no.1
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• pp.189-216
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• 2019

The frequent occurrence of overwhelming disasters necessitates risk communication systems capable of operating effectively in disaster contexts. Few studies have examined risk communication networks during disasters through social networking services (SNS). This study therefore investigates the patterns of risk communication by comparing Korean and international networks based on the social amplification of risk communication in the context of the Sewol ferry disaster (SFD). In addition, differences in language use and patterns between Korean and international contexts are identified through a semantic analysis using KrKwick, NodeXL, and UCINET. The SFD refers to the sinking of the ferry while carrying 476 people, mostly secondary school students. The results for interpersonal risk communication reveal that the structure of the Korean risk communication network differed from that of the international network. The Korean network was more fragmented, and its clustering was more sparsely knitted based on the impact and physical proximity of the disaster. Semantic networks imply that the physical distance from the disaster affected the content of risk communication, as well as the network pattern.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4706-4724
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• 2020

With various structured data, such as the company size, loan balance, and savings accounts, the voice of customer (VOC), which is text data containing contact history and counseling details was analyzed in this study. To analyze unstructured data, the term frequency-inverse document frequency (TF-IDF) analysis, semantic network analysis, sentiment analysis, and a convolutional neural network (CNN) were implemented. A performance comparison of the models revealed that the predictive model using the CNN provided the best performance with regard to predictive power, followed by the model using the TF-IDF, and then the model using semantic network analysis. In particular, a character-level CNN and a word-level CNN were developed separately, and the character-level CNN exhibited better performance, according to an analysis for the Korean language. Moreover, a systematic selection model for optimal text mining techniques was proposed, suggesting which analytical technique is appropriate for analyzing text data depending on the context. This study also provides evidence that the results of previous studies, indicating that individual customers leave when their loyalty and switching cost are low, are also applicable to corporate customers and suggests that VOC data indicating customers' needs are very effective for predicting their behavior.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.242-248
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• 2022

The article presents the analysis of modern methods of automatic comparison of original and unoriginal text to detect textual plagiarism. The study covers two types of plagiarism - literal, when plagiarists directly make exact copying of the text without changing anything, and intelligent, using more sophisticated techniques, which are harder to detect due to the text manipulation, like words and signs replacement. Standard techniques related to extrinsic detection are string-based, vector space and semantic-based. The first, most common and most successful target models for detecting literal plagiarism - N-gram and Vector Space are analyzed, and their advantages and disadvantages are evaluated. The most effective target models that allow detecting intelligent plagiarism, particularly identifying paraphrases by measuring the semantic similarity of short components of the text, are investigated. Models using neural network architecture and based on natural language sentence matching approaches such as Densely Interactive Inference Network (DIIN), Bilateral Multi-Perspective Matching (BiMPM) and Bidirectional Encoder Representations from Transformers (BERT) and its family of models are considered. The progress in improving plagiarism detection systems, techniques and related models is summarized. Relevant and urgent problems that remain unresolved in detecting intelligent plagiarism - effective recognition of unoriginal ideas and qualitatively paraphrased text - are outlined.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.95-101
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• 2022

The development of the 4th industry has increased social media, and the rise of COVID-19 has stimulated non-face-to-face services. People's consumption patterns are also changing a lot due to non-face-to-face services. In this paper, food content keywords are derived through social network-based semantic network analysis, emotions are analyzed, and keywords applied to food recommendation platforms are input. We collected food, influencer, and corona keyword analysis data through Textom. A lot of research has been done through online reviews of existing influencer content. However, there is a lack of research on keyword sentiment analysis provided by influencers rather than consumers and research perspectives. This paper uploads language and topics derived through online reviews of existing publications and subscribers, and goes beyond the limits used in marketing methods. By analyzing keywords that influencers suggest when uploading content, you can apply data that applies them to food recommendation platforms and applications.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.1137-1144
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• 2009

Creativity, the ability to produce through imaginative skill, is pursued by all designers. However, originality does not refer to absolute novelty. In this age, information is shared and disseminated. Creation of works is an activity to re-establish all shared information and reorganize relationship among things. Therefore, a new design is a product of reorganization rather than originality. Moreover, designers can generate ideas different from each other because they individually espouse different system of knowledge. From such perspective, a very important task of designers is to explore methods of expanding design thinking that can enhance the ability to new connection among things in the process of assimilation and modification. The task can be carried out by identifying characteristics and limits of their unique system of knowledge. Therefore, it is necessary to seek methods of expanding design thinking for efficient cognitive activities. In explaining human knowledge, this study applied semantic network, a method used in cognitive science for creating structure, and the method of expanding design thought was proposed by corresponding method of design conceptualization. By organizing, categorizing, and flexibly combining and modifying the methods of design thinking conceptualization and expansion generated by this study, strengths of each method were enhanced and limits of each method were overcome to enable more effective design thinking. In this study, the method of expansion was used when connecting of nodes cannot be sustained after using each method of conceptualization. By avoiding unique method of thinking through diversification and vitalization of conditional points, efficient design thinking was achieved. The value of this study lies in the fact that the proposed method of expanding thinking using the mechanism of network enhances the ability to establish new connections in the process of assimilation and modification.

• Journal of Gifted/Talented Education
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• v.25 no.2
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• pp.195-216
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• 2015

Students' perceived values of career play a core role in formation of their career motivation. In particular, science gifted students should build sound values of career in science and technology so that our society can retain the human resources for future science and technology. This study compared and analyzed the structure of science gifted and general middle school students' preferred job and values of career using semantic network analysis. Methodologically, we first collected science gifted and general middle school students' preferred careers and the reasons of the career choice using survey method. Then, we structuralize semantic networks of students' perceived values of their preferred careers using semantic network analysis. We identified the characters of networks that two different student groups showed based on the structure matrix indices of semantic network analysis. Findings revealed that science gifted students considered the creativeness as the most important value of career. Second, science gifted students considered more diverse values of career than general students. Third, science gifted students considered the self-realization such as displaying capability as a core value of career in STEM and medical science whereas general students considered the community service as a core value of the careers. This study identified the significant differences between science gifted and general middle school students' values of careers. The structures of students perceived values of careers can be used for teachers to counsel their students about students' future careers.

• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.67-79
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• 2007

As the Web technologies and wired/wireless network are improved and various new multimedia services are introduced recently, need for searching multimedia including video data has been much increasing, The previous approaches for multimedia retrieval, however, do not make use of the relationships among semantic concepts contained in multimedia contents in an efficient way and provide only restricted search results, This paper proposes a multimedia retrieval system exploiting semantic relevancy of multimedia contents based on a domain ontology, We show the effectiveness of the proposed system by experiments on a prototype system we have developed. The proposed multimedia retrieval system can extend a given search keyword based on the relationships among the semantic concepts in the ontology and can find a wide range of multimedia contents having semantic relevancy to the input keyword. It also presents the results categorized by the semantic meaning and relevancy to the keyword derived from the ontology. Independency of domain ontology with respect to metadata on the multimedia contents is preserved in the proposed system architecture.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1807-1824
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• 2015

As the technologies advance, mobile peer-to-peer (MP2P) networks or systems become one of the major ways to share resources and information. On such a system, the information retrieval (IR), including the development of scalable infrastructures for indexing, becomes more complicated due to a huge increase on the amount of information and rapid information change. To keep the systems on MP2P networks more reliable and consistent, the index structures need to be updated frequently. For a semantic IR system, the index structure is even more complicated than a classic IR system and generally has higher update cost. The most well-known indexing technique used in semantic IR systems is Latent Semantic Indexing (LSI), of which the index structure is generated by singular value decomposition (SVD). Although LSI performs well, updating the index structure is not easy and time consuming. In an MP2P environment, which is fully distributed and dynamic, the update becomes more challenging. In this work, we consider how to update the sematic index generated by LSI and keep the index consistent in the whole MP2P network. The proposed Concept Space Update (CSU) protocol, based on distributed 2-Phase locking strategy, can effectively achieve the objectives in terms of two measurements: coverage speed and update cost. Using the proposed effective synchronization mechanism with the efficient updates on the SVD, re-computing the whole index on the P2P overlay can be avoided and the consistency can be achieved. Simulated experiments are also performed to validate our analysis on the proposed CSU protocol. The experimental results indicate that CSU is effective on updating the concept space with LSI/SVD index structure in MP2P semantic IR systems.