• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.12
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• pp.1604-1610
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• 2018

The speech recognition service is used as an ancillary means of communication by converting and visualizing the speaker's voice into text to the hearing impaired persons. However, in open environments such as classrooms and conference rooms it is difficult to provide speech recognition service to many hearing impaired persons. For this, a method is needed to efficiently provide it according to the surrounding environment. In this paper, we propose a system that recognizes the speaker's voice and transmits the converted text to many hearing impaired persons as messages. The proposed system uses the MQTT protocol to deliver messages to many users at the same time. The end-to-end delay was measured to confirm the service delay of the proposed system according to the QoS level setting of the MQTT protocol. As a result of the measurement, the delay between the most reliable Qos level 2 and 0 is 111ms, confirming that it does not have a great influence on conversation recognition.

• Journal of Creative Information Culture
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• v.6 no.2
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• pp.57-64
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• 2020

As the information society gradually advances, various opinions overflow and their complexity increases. As the results, it was made more difficult to derive important issues and properly respond to those problems. Accordingly, it is necessary to get a handle on emerging problems in education in addition to existing discourses and issues. This study aimed at examining the issues of education by analyzing the petitions posted under 'parenting and education' category on National Petition board. In order to offer objective and detailed results, we employed the topic modeling based LDA algorithm, which is an effective method to extract topics in multiple documents. Nine topics were derived as the result of the analysis and the relationship among those topics was visualized. The values of this study exist in that the derived topics represent important issues that reflect the public opinions.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.287-294
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• 2022

The purpose of this study is to find out consumers' perceptions of "metaverse," a newly spotlighted technology, through big data analysis as a non-face-to-face society continues after the outbreak of COVID-19. This study conducted a big data analysis using text mining to analyze consumers' perceptions of metaverse before and after COVID-19. The top 30 keywords were extracted through word purification, and visualization was performed through network analysis and concor analysis between each keyword based on this. As a result of the analysis, it was confirmed that the non-face-to-face society continued and metaverse emerged as a trend. Previously, metaverse was focused on textual data such as SNS as a part of life logging, but after that, it began to pay attention to virtual reality space, creating many platforms and expanding industries. The limitation of this study is that since data was collected through the search frequency of portal sites, anonymity was guaranteed, so demographic characteristics were not reflected when data was collected.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.491-498
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• 2022

In this paper, as a liberal arts course for non-major students, a case study of recurrent neural network SW practice, which is essential for designing a basic recurrent neural network subject curriculum, was developed. The developed SW practice case focused on understanding the operation principle of the recurrent neural network, and used a spreadsheet to check the entire visualized operation process. The developed recurrent neural network practice case consisted of creating supervised text completion training data, implementing the input layer, hidden layer, state layer (context node), and output layer in sequence, and testing the performance of the recurrent neural network on text data. The recurrent neural network practice case developed in this paper automatically completes words with various numbers of characters. Using the proposed recurrent neural network practice case, it is possible to create an artificial intelligence SW practice case that automatically completes by expanding the maximum number of characters constituting Korean or English words in various ways. Therefore, it can be said that the utilization of this case of basic practice of recurrent neural network is high.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.6
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• pp.974-979
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• 2002

There are so many kind of a control program that is applied in various process fields such as power generation plant, water treatment plant, incinerator plant, chemical plant, cement plant etc.. Because an engineer in field edits and changes and debugs and tests properly control programs using text-based control language, it is very hard for the him to apply to plant. Therefore, this research implemented a graphical tool for control program builder that is applicable to various plants and usable engineers having a little knowledge for control language. I wish to run more efficiently precision process control offering function that can see visual expression about flow of control signal and intermediate output values of control program displayed in screen using this implemented function block builder.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.325-330
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• 2008

전자우편(email)은 인터넷의 급격한 보급으로 인하여 사용자들이 많이 사용하게 된 통신 메커니즘이다. 그러나 이러한 전자우편의 대중성을 상업적인 목적으로 이용한 스팸메일의 출현으로, 사용자들은 정신적 피해, 업무 방해, 메일서버의 트래픽 과부화로 인한 유지보수 비용 증가와 같은 문제점들을 접하게 되었다. 특히, 최근에는 광고성 이미지들을 첨부하는 등의 새로운 기법이 적용된 스팸메일의 발생으로 기존의 텍스트 기반의 스팸메일 필터링 기법들이 무의미하게 되었으며, 따라서 그로 인한 피해가 증가하는 추세이다. 이러한 이미지 기반의 스팸메일들의 필터링을 위하여 Support Vector Machine과 같은 기계학습 기법을 이용한 기법들이 제안되고 있으나, 여전히 그 성능은 만족스럽지 못하다. 본 논문은 전자우편으로부터 텍스트 및 시각적 의미를 분석하여 전자우편 온톨로지에 기술하고 스팸메일 판단을 위한 의미추론규칙을 적용함으로써 광고성 이미지가 첨부되어 있는 스팸메일을 효과적으로 필터링 하기 위한 시스템을 제안한다.

• Information Systems Review
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• v.18 no.1
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• pp.141-155
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• 2016

This study identified terminologies related to the proximity and frequency of disaster by social network analysis (SNA) and text mining, and then expressed the outcome into a mind map. The termdocument matrix of text mining was utilized for the terminology proximity analysis, and the SNA closeness centrality was calculated to organically express the relationship of the terminologies through a mind map. By analyzing terminology proximity and selecting disaster response-related terminologies, this study identified the closest field among all the disaster response fields to disaster response and the core terms in each disaster response field. This disaster response terminology analysis could be utilized in future core term-based terminology standardization, disaster-related knowledge accumulation and research, and application of various response scenario compositions, among others.

• Information Systems Review
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• v.20 no.2
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• pp.139-161
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• 2018

As Korea became one of the oldest countries in the world, successful aging emerged as an important issue to individuals as well as to society. This study aims to determine not only the Korean seniors' happiness and unhappiness factors but also the means to enhance their happiness and deal with unhappiness. We collected news articles related to the happiness and unhappiness of seniors with nine keywords based on Alderfer's ERG Theory. We then applied a topic modeling technique, Latent Dirichlet Allocation, to examine the main issues underlying the seniors' happiness and unhappiness. According to the analysis, we investigated the conditions of happiness and unhappiness by inspecting the topics based on each keyword. We also conducted a detailed analysis based on the main factors from topic modeling. We proposed specific ways to increase and overcome the happiness and unhappiness of seniors, respectively, in terms of government, corporate, family, and other social welfare organizations. This study indicates the major factors that affect the happiness and unhappiness of seniors. Specific methods to boost happiness and relief unhappiness are suggested from the additional analysis.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.49-56
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• 2014

In this paper, we propose a method for identifying hidden principal sentiments among large scale texts from documents, social data, internet and blogs by analyzing standard language, slangs, argots, abbreviations and emoticons in those words. The IRLBA(Implicitly Restarted Lanczos Bidiagonalization Algorithm) is used for principal component analysis with large scale sparse matrix. The proposed system consists of data acquisition, message analysis, sentiment evaluation, sentiment analysis and integration and result visualization modules. The suggested approaches would help to improve the accuracy and expand the application scope of sentiment analysis in social data.

• 한국만화애니메이션학회:학술대회논문집
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• 2011.05a
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• pp.23-30
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• 2011

지금, 세계는 바야흐로 'Social Network Service(이하 SNS)의 시대' 이다. SNS란 '일련의 관계에 의해 모인 사람들 간의 관계망을 특정 체계를 통해 대중에게 제공하는 것' 이라고 할 수 있다. 과거 향우회, 동문회처럼 오프라인에서 존재했던 이러한 관계망이 온라인으로 도입된 것이 현재 SNS라고 일컫는 서비스이다. SNS가 큰 인기를 끌고 정보 사회가 발전함에 따라 SNS의 서비스와 형태도 점차 다양해져 왔다. 특히나 그림 영상 등의 시각적인 요소를 사용한 의사소통과 정보의 공유가 과거 그 어떤 매체보다도 손쉽고 빠르게 이루어지고 있다. 인간의 거의 모든 문화 사회적 활동에 컴퓨터가 기반이 됨으로써, 우리는 점차 텍스트, 사진, 영화, 음악, 가상환경 등과 같은 문화 데이터와 더욱 밀접한 관계에 놓이게 되었으며 이것은 SNS에서도 예외가 아니다. 우리는 더 이상 컴퓨터를 마주하는 것이 아니라 디지털 형식으로 기호화된 문화와 마주하고 있으며, 그 중심에는 시각적인 요소들, 즉 '이미지'가 있다. 이러한 점에 착안하여 본 연구는 'SNS'와 그 이미지들의 특성에 대한 이해를 선행한 뒤, 최근 국내에서 가장 활발한 성장세를 나타내고 있는 SNS인 미투데이 페이스북 이상의 두 서비스의 사례를 분석할 것이다. SNS의 이미지의 정체성, 이미지 표현의 특징과 양상이 어떠한지를 분석하고 SNS에서 사용되는 이미지와 그 의미를 보다 심층적인 관점에서 이해해 보는 것은 SNS를 중심으로 형성되어 있는 관련 업계와 학계에 유의미한 내용을 제공할 것으로 기대된다.