• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1637-1646
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• 2009

Recently many researchers have been studying various methods for data integration. Among the integration methods that the researchers have studied, there are a method using metadata repository, and Topic Map which identifies the relationships between the data. This study suggests Meta-Topic Map to create Topic Map about search keyword by applying metadata and Topic Map, and the XMDR as a way to connect Meta-Topic Map with metadata in the legacy system. Considering the semantic relationship of user's keyword in the legacy system, the Meta-Topic Map provides the Topic Map format and generates the Topic Map about user's keyword. The XMDR performs structural integration through solving the problem of heterogeneity among metadata in the legacy system. The suggested svides isproves the interoperability among existing Relational Database constructed in the legacy system and the search efficiency and is efficient in expanding the system.

• KIISE Transactions on Computing Practices
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• v.22 no.2
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• pp.83-88
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• 2016

Subtopic mining is the extraction and ranking of possible subtopics, which disambiguate and specify the search intentions of an input query in terms of relevance, popularity, and diversity. This paper describes the limitations of previous studies on the utilization of web resources, and proposes a subtopic mining method with a two-level hierarchy based on hierarchical search intentions and web resources, in order to overcome these limitations. Considering the characteristics of resources provided by the official subtopic mining task, we extract various second-level subtopics reflecting hierarchical search intentions from web documents, and expand and re-rank them using other provided resources. Terms in subtopics with wider search intentions are used to generate first-level subtopics. Our method performed better than state-of-the-art methods in almost every aspect.

• Smart Media Journal
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• v.10 no.4
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• pp.102-110
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• 2021

Currently, the advanced construction technology endorsement system is being operated to promote the development of domestic construction technology. We tried to examine the implicit meanings inherent in advanced construction technologies by analyzing the relationship between emerging vocabularies with high importance in relation to the advanced construction technologies endorsed through this system. For this purpose, 918 cases of advanced construction technology information were collected. Based on the endorsed year and summary of the advanced construction technologies, the importance of the emerging vocabularies was measured for each advanced construction technology. And, based on the LDA model, the degree of influence between related vocabularies was evaluated for each of the four topic areas. Topics according to the technical application fields were analyzed. From 1990 to 2021, the trend of changes in highly influential vocabularies by each topic was inferred. In the future, changes in the degree of influence of the topics of environment, machinery, facilities, and maintenance and reinforcement of structures and related technology fields were predicted.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.50-59
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• 2021

To understand the research trends of English education in Korea for the last 20 years from 2000 to 2019, 12 major academic journals in Korea in the field of English education were selected, and bibliographic information of 7,329 articles published in these journals were collected and analyzed. The total number of articles increased from the 2000s to the first half of the 2010s, but decreased somewhat in the late 2010s and the number of publications by journal has become similar. These results show that the overall influence of English education journals has decreased and then leveled in terms of quantity. Next, 34 topics were extracted by applying latent Dirichlet allocation (LDA) topic modeling using the English abstract of the articles. Teacher, word, culture/media, and grammar appeared as topics that were highly studied. Topics such as word, vocabulary, and testing and evaluation appeared through unique keywords, and various topics related to learner factors emerged, becoming topics of interest in English education research. Then, topics were analyzed to determine which ones were rising or falling in frequency. As a result of this analysis, qualitative research, vocabulary, learner factor, and testing were found to be rising topics, while falling topics included CALL, language, teaching, and grammar. This change in research topics shows that research interests in the field of English education are shifting from static research topics to data-driven and dynamic research topics.

• Journal of KIISE
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• v.43 no.11
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• pp.1201-1209
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• 2016

As the use of SNS continues to increase, various related studies have been conducted. According to the effectiveness of the topic model for existing theme extraction, a huge number of related research studies on topic model based analysis have been introduced. In this research, we suggested an automation system to analyze topics of each country and its distribution in twitter by combining world map visualization and issue matching method. The core system components are the following three modules; 1) collection of tweets and classification by nation, 2) extraction of topics and distribution by country based on topic model algorithm, and 3) visualization of topics and distribution based on Google geochart. In experiments with USA and UK, we could find issues of the two nations and how they changed. Based on these results, we could analyze the differences of each nation's position on ISIS problem.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.685-689
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• 2009

Evolutionary Computation is not only widely used in optimization and machine learning, but also being applied in creating novel structures and entities. This paper proposes evolutionary topic maps that can suggest new and creative knowledge not easily producible by humans. Interactive evolutionary computation method is applied into topic maps in order to accept human evaluation on feasibility of intermediate topic maps. Evolutionary topic maps are creativity support tools, helping users to encounter new and creative knowledge. Further work can greatly improve the system by providing more operations, preventing over-convergence, and overcoming user fatigue problem by providing more intuitive user interface, better visualization, and interpolation mechanisms.

• Annual Conference on Human and Language Technology
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• 2015.10a
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• pp.228-230
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• 2015

방송 대본은 방송 콘텐츠에 대해 얻을 수 있는 가장 주요한 텍스트 데이터 중에 하나이다. 본 논문에서는 토픽 모델을 통해 방송 대본 분석을 수행하고 그 결과를 제시한다. 방송 대본을 토픽 모델로 학습하기 위해 대본의 장면 단위로 문서를 구성하여 학습하여 대본의 장면을 분석하고 등장인물 단위로 문서를 구성하여 등장인물을 분석하여 그 특징을 살펴본다. 토픽 모델을 사용하여 방송 대본을 분석하는 과정에서 방송 대본이 가지는 특징을 분석하고 그로부터 향후 연구방향에 대해 논의한다.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.47-56
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• 2021

The purpose of this study is to use network analysis to identify trends in university personality-related studies and provide implications for future research directions. For the purpose of this study, 194 papers related to personality of university students published in Korean scholarly journals. First, research began to be published in 2004, slightly increased in 2012, continued an upward curve from 2015, peaked in 2017, and is confirmed to be a downward trend. Second, the main keywords with the centrality analysis were 'society' and 'cultivation'. Third, keywords on the cognitive side and individual dimension of personality in the first period (2004 - 2010), social dimension and emotional side of personality in the second period (2011-2015), and social level and cognitive, emotional, and behavioral aspects of personality in the third period (2016-2020). Fourth, Topic 2 consisted of keywords of ability, life, interpersonal, satisfaction, and adaptation, and Topic 1 consisted of competence, morality, citizens, society, and practice. Fifth, Topic 4 alone in the first period, in the order of Topic 1 and Topic 2 in the second period, and in the order of Topic 2 and Topic 1 in the third period.

• Journal of Energy Engineering
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• v.29 no.2
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• pp.23-29
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• 2020

In this study, the last 10 years of news data on fine dust was collected and 80 topics are selected through LDA analysis. As a result, weather-related information made up the main words for the topic, and we can see that fine dust becomes a big issue below 10 degrees Celsius. The frequency of exposure to the media and the maximum concentration of fine dust are correlated with positive. Topics related to fine dust reduction measures and the government's comprehensive measures over the past decade, topics related to products such as air purifiers related to fine dust, topics related to policies protecting vulnerable people from fine dust, and topics on fine dust reduction through R&D were found to be major topics. Measures against fine dust as a social issue can be seen to be closely related to the government's policy.

• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.119-129
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• 2016

With the development of web, amount of information are generated in social web. Then many researchers are focused on the extracting and analyzing social issues from various social data. The proposed approach performed gathering the science data and analyzing with LDA algorithm. It generated the clusters which represent the social topics related to 'health'. As a result, we could deduce the relationship between science data and social issues.