• The KIPS Transactions:PartB
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• v.11B no.7 s.96
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• pp.793-802
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• 2004

Users in 3D virtual environment get limited information which contains mostly images. It is the main reason for users getting lost during their Navigation. Various studies of Navigation-Aid have been done in order to solve this problem. In this study, we applied Topic Maps, which is one of semantic Web techniques, to the navigation in a 3D virtual environment. Topic Maps construct semantic linking maps through defining the relations between topics. Experiments in which Topic Map based Navigation-Aid was applied have shown that the Navigation-Aid was effective when the subjects find a detailed target rather than a highly represented one. Also, offering information around the target helped the users to find the target when they navigated without having specific targets.

• Journal of the Korea Convergence Society
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• v.8 no.10
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• pp.249-255
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• 2017

The domestic tourism industry mostly relies on quantitative surveys for customer satisfaction. However, customer participation of the questionnaires is extremely low and the improvement of the dissatisfactory factors is not being performed promptly. In this paper, we propose a new topic map system and prove its empirical effectiveness to improve the accuracy of customer feedback information and the efficiency of the analysis process. The topic map system is a system for analyzing large amounts of customer feedback data in real time. It uses text mining and ontology techniques by integrating data collected over a certain period from real-time SNS and quantitative data obtained from existing survey systems. The effect after improving the analyzed factors of dissatisfaction is also a new and innovative evaluation system for monitoring customer satisfaction in real time. The classification based on this integrated data is a classification system that is specific to the product or the customer. According to this classification, it is possible to measure the effect of the recognition and improvement of the complaint factor in real time on the topic map system. This provides a sophisticated prioritization of the improvement factors and enables customer satisfaction quality control as a PDCA feedback system. In addition, the survey period and costs are greatly shortened, and responses can be more precise to the existing survey method. As a practical application, this system is applied to the largest H travel agency in Korea to prove the accuracy and efficiency of the proposed system.

• New & Renewable Energy
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• v.16 no.4
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• pp.33-40
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• 2020

The research topics of more than 1,900 wind energy papers registered in the Korean Journal Citation Index (KCI) were modeled into 25 topics using latent directory allocation (LDA), and their consistency was cross-validated through principal component analysis (PCA) of the document word matrix. Key research topics in the wind energy field were identified as "offshore, wind farm," "blade, design," "generator, voltage, control," 'dynamic, load, noise," and "performance test." As a new method to determine the similarity between research topics in journals, a systematic evaluation method was proposed to analyze the correlation between topics by constructing a journal-topic matrix (JTM) and clustering them based on topic similarity between journals. By evaluating 24 journals that published more than 20 wind energy papers, it was confirmed that they were classified into meaningful clusters of mechanical engineering, electrical engineering, marine engineering, and renewable energy. It is expected that the proposed systematic method can be applied to the evaluation of the specificity of subsequent journals.

• Journal of Advanced Navigation Technology
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• v.13 no.2
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• pp.296-301
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• 2009

In the self-directed learning, learner can construct learning course. But it is very difficult for learner to construct learning course with understanding the various learning contents's characteristics. This research proposed the method to support to learner the information of learning contents type to fit the learner as calculate the learner's learning preference when learner construct the learning course. The calculating method of learning preference used preference vector value of topic map. To apply this method, we tested 20 learning sampling group and presented that this method help to learner to construct learning course as getting the high average degree of learning satisfaction.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.2
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• pp.289-307
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• 2016

Infectious diseases such as Ebola virus disease become a social issue and draw public attention to be a major topic on news or research. As a result, there have been a lot of studies on infectious diseases using text-mining techniques. However, there is no research on content analysis of two media channels that have distinct characteristics. Accordingly, in this study, we conduct topic analysis between news (representing a social perspective) and academic research paper (representing perspectives of bio-professionals). As text-mining techniques, topic modeling is applied to extract various topics according to the materials, and the word co-occurrence map based on selected bio entities is used to compare the perspectives of the materials specifically. For network analysis, topic map is built by using Gephi. Aforementioned approaches uncovered the difference of topics between two materials and the characteristics of the two materials. In terms of the word co-occurrence map, however, most of entities are shared in both materials. These results indicate that there are differences and commonalties between social and academic materials.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.213-218
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• 2012

Modern culture has describing the year's situation along the social environment. A literary work changed as if the year's situation change. Therefore we can understand the age through the literary work and get knowledge the social request of the year's. This literary works have made a chance to know approaching more closely to user as producing media resources. Recently, IT convergence and digital convergence become a new trend to combine each other academic area and get much synergy effect. In this paper, we propose an application and design of the ontology that needs to make digital content from modern literary work's information. For this works, we specify the structure of the year's literary work and the relation of each factor. The specification method used topic map. Each relation model was specified the connection by topic vector.

• The Korean Journal of Health Service Management
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• v.11 no.4
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• pp.213-224
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• 2017

Objectives : The purpose of this study was to analyze representative topics and topic trends of papers in Korean Society and Health Service Management(KSHSM) Journal. Methods : We collected English abstracts and key words of 516 papers in KSHSM Journal from 2007 to 2017. We utilized Python web scraping programs for collecting the papers from Korea Citation Index web site, and RStudio software for topic analysis based on latent Dirichlet allocation algorithm. Results : 9 topics were decided as the best number of topics by perplexity analysis and the resultant 9 topics for all the papers were extracted using Gibbs sampling method. We could refine 9 topics to 5 topics by deep consideration of meanings of each topics and analysis of intertopic distance map. In topic trends analysis from 2007 to 2017, we could verify 'Health Management' and 'Hospital Service' were two representative topics, and 'Hospital Service' was prevalent topic by 2011, but the ratio of the two topics became to be similar from 2012. Conclusions : We discovered 5 topics were the best number of topics and the topic trends reflected the main issues of KSHSM Journal, such as name revision of the society in 2012.

• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.819-828
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• 2007

In this paper, we propose a topic maps matching and merging approach based on the syntactic or semantic characteristics and constraints of the topic maps. Previous schema matching approaches have been developed to enhance effectiveness and generality of matching techniques. However they are inefficient because the approaches should transform input ontologies into graphs and take into account all the nodes and edges of the graphs, which ended up requiring a great amount of processing time. Now, standard languages for developing ontologies are RDF/OWL and Topic Maps. In this paper, we propose an enhanced version of matching and merging technique based on topic partitioning, several matching operations and merging conflict detection.

• Sijohaknonchong
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• v.19 no.1
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• pp.37-62
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• 2003

This treatise discuss the possibility and prospect for developing Sijo Munhwa information system. The contents of it is summarized as follows. 1. We must gather and input correctly materials including original texts to develope Sijo Munhwa information system as linguistic data. 2. We must consider TEI(Text Encoding Initiative) and thesauras when we process the database. 3. 2 form the ground work of building Topic Map. 4. It's very important to link Sijo Munhwa information system as art material with visual or auditory images in three dimensions completely.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.289-293
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• 2006

국내에서도 표준화 작업이 진행 중인 토픽맵은 분산된 정보와 지식의 관리를 지원하기 위한 국제 표준이다. 이 논문에서는 이클립스(Eclipse) 플랫폼의 플러그인 개발환경인 GMF를 이용하여 비교적 작은 도메인에 대한 토픽맵의 구조를 도식화된 방법으로 표현하고, 간편하고 직관적인 편집기능을 사용자에게 제공하며, 이러한 구조의 간단한 프로토타입 정보라 할 수 있는 Linear Topic Map Notation(LTM)을 만들어 내는 플러그 인을 소개할 것이다.