• 한국IT서비스학회지
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• 제13권3호
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• pp.323-331
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• 2014

This research is based on real-time service model that uses lock screen of smart devices which is mostly exposed to device users. The potential for lock screen space is immense due to their exposing time for user. The effect can be maximized by offering useful information contents on lock screen. This service model offers real-time keyword with abridged sentence. They match real-time keyword with news by using text matching algorithm and extracts kernel sentence from news to provide short sentence to user. News from the lock screen to match real-time query sentence, and then only to the original core of the ability to move a user evaluation was conducted after adding. The report provided a key statement users feel the lack of original Not if you go to an average of 5.71%. Most algorithms allow only real-time zoom key sentence extracted keywords can accurately determine the reason for that was confirmed.

• International journal of advanced smart convergence
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• 제7권4호
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• pp.147-153
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• 2018

This study is about the interactive self-portrait which provides the experience of self-consciousness reflection of the viewer to modern people who are easily alienated in rapid social change. We proposed interactive self-portrait is implemented by an interactive mirror that reproduces the appearance of the viewer acquired using a webcam. The interactive mirror, which can directly project its own image, is drawn by searching news articles in real time and using the extracted characters as pixel information in real time. The viewer has the opportunity to experience a new style of active self-expression while watching his/herself composed of news characters that are issues of modern society. The virtual self-portrait designed with news characters can attract viewers' attention by visually expressing the interests of modern people and can act as an incentive to generate positive interaction.

• 디지털콘텐츠학회 논문지
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• 제19권4호
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• pp.631-637
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• 2018

신문기사를 읽기 위하여 종이 신문의 이용은 줄고 스마트폰을 이용하는 경우가 많아지고 있어 뉴스 어플리케이션은 늘고 있다. 안드로이드 플레이 스토어의 많은 뉴스 어플리케이션은 2가지로 분류된다. 첫 번째는 특정 신문사에서 개발하여 해당 신문사의 기사만 배포하는 것이고, 나머지는 신문 목록을 보여주고 신문을 선택하면 신문사 홈페이지를 보여주는 것이다. 본 논문에서는 국내의 많은 신문사의 기사를 모아서 실시간으로 제공하기 위한 실시간뉴스 어플리케이션을 설계 및 구현하였다. 신문사들은 제공하는 RSS로 최신 기사를 제공한다. 서버프로그램은 최신기사를 시간 순으로 정렬하여 DB에 저장하고 실시간뉴스 어플리케이션에서 요구하는 기사를 실시간으로 전송한다. 최신 뉴스를 보기 위해 여러 곳에 분산된 신문사의 홈페이지를 각각 방문하지 않고도 각 신문사의 기사를 모아서 볼 수 있고 각 홈페이지를 접속하는데 사용되는 데이터의 사용을 줄일 수 있는 장점이 있다.

• 한국콘텐츠학회논문지
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• 제20권6호
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• pp.556-578
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• 2020

실시간으로 발생하는 뉴스 기사로부터 이슈를 분석하기 위한 다양한 연구가 진행되어 왔다. 하지만 범주에 따라 계층적으로 이슈를 분석하는 연구는 많이 진행되지 않았고, 계층적 이슈 분석을 위한 기존의 연구에서 제안하는 방식 또한 뉴스 기사 증가에 따라 군집화 속도가 느려지는 문제점이 있다. 따라서 본 논문에서는 준 실시간으로 뉴스 기사의 이슈를 분석하는 계층적·점증적 군집화 방식을 제안한다. 제안하는 군집화 방식은 샴 신경망을 이용한 가중 코사인 유사도 측정 모델 기반의 k-평균 알고리즘을 이용한 단어 군집 기반 문서 표현 방식을 통해 뉴스 기사를 문서 벡터로 표현한다. 그리고 문서 벡터로부터 초기 이슈 군집 트리를 생성하고, 새로 발생한 뉴스 기사를 해당 이슈 군집 트리에 추가하는 점증적 군집화 방식을 제안함으로써 뉴스 기사의 계층적 이슈를 준 실시간으로 분석한다. 마지막으로, 본 논문에서 제안하는 방식과 기존 방식들과의 성능평가를 통해 제안하는 군집화 방식이 정확도 측면에서 기존 방식 대비 NMI 지표 기준 0.26 정도 성능이 향상되었고, 속도 측면에서 약 10배 이상의 성능이 향상됨을 입증하였다.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2006년도 춘계 학술대회 발표논문집
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• pp.89-93
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• 2006

This paper presents ETRI broadcast news speech recognition system. There are two major issues on the broadcast news speech recognition: 1) real-time processing and 2) out-of-vocabulary handling. For real-time processing, we devised the dual decoder architecture. The input speech signal is segmented based on the long-pause between utterances, and each decoder processes the speech segment alternatively. One decoder can start to recognize the current speech segment without waiting for the other decoder to recognize the previous speech segment completely. Thus, the processing delay is not accumulated. For out-of-vocabulary handling, we updated both the vocabulary and the language model, based on the recent news articles on the internet. By updating the language model as well as the vocabulary, we can improve the performance up to 17.2% ERR.

• 한국멀티미디어학회논문지
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• 제21권3호
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• pp.415-422
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• 2018

Advances of telecommunication technology bring various changes in journalism field. Reporters started to gather, edit, and transmit content to main server in media company using hand-held smart media and notebook computer. This paper tried to testify valid bit-rate of visual news content using LTE network and mobile phone. Field news like natural disasters need real-time transmission of video content. But broadcasting company normally use heavy ENG system and transmission satellite trucks. We prepared and experimented different types of visual content that has different bit-rates. Transmission tool was LU-60HD mobile system of LiveU Corporation. Transmission result shows that bit-rate of 2Mbps news content is not suitable for broadcasting and VBR (Variable Bit Rate) transmission has better definition quality than CBR (Constant Bit Rate) method. Three different bit-rate of VBR transmission result shows that 5Mbps clip has better quality than 1Mbps and 3Mbps. The higher bit-rate, the better video quality. But if the content has much movements, that cause delay and abnormal quality of video. So optimizing the balance between stability of signal and quality of bit-rate is crucial factor of real-time broadcasting news gathering business.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제7권10호
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• pp.251-258
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• 2018

파일을 암호화시켜 몸값을 요구하는 악성 소프트웨어인 랜섬웨어는 빠른 전파력과 지능화로 더욱 위협적이 되고 있다. 이에 빠른 탐지 및 위험 분석이 요구되고 있지만, 실시간 분석 및 보고가 미비한 상태이다. 본 논문에서는 실시간 분석이 가능하도록 소셜 빅데이터 마이닝 기술을 활용하여 랜섬웨어 전파 감지 시스템을 제안한다. 본 시스템에서는 트위터 스트림을 실시간 분석하여 랜섬웨어와 관련된 키워드를 가진 트윗을 크롤링한다. 또한 뉴스피드 분석기를 통해 뉴스서버를 크롤링하여 랜섬웨어 관련 키워드를 추출하고, 보안업체의 서버나 탐색 엔진을 통해 뉴스나 통계데이터를 추출한다. 수집된 데이터는 데이터 마이닝 알고리즘으로 랜섬웨어 감염 정도를 분석한다. 2017년 전파가 많이 되었던 워너크라이와 록키 랜섬웨어 감염전파 시 관련 트윗의 수와 구글 트렌드(통계 정보) 정보, 관련 기사를 비교하여 트윗을 이용한 본 시스템의 랜섬웨어 감염 탐지 가능성을 보이고, 엔트로피와 카이-스퀘어 분석을 통해 제안 시스템 성능을 보인다.

• International Journal of Advanced Culture Technology
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• 제6권2호
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• pp.65-71
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• 2018

In the digital era, news consumption is not confined in geological boundaries. Technological advances bring the instant dissemination of news into life and allow news audience to consume events that occur far away almost in real time. The transmission has blurred the boundary between traditional media and new media, and the one between physical and virtual world. That is, what if a journalist applies news framing to the news translation process? This paper aims to investigate the gap between the ST and the TT created when the source news texts undergo a translation process. To achieve this aim, the appraisal theory developed by White (2003) is employed to identify a difference between the ST and the TT. Furthermore, we have attempted to identify differences between soft news stories and hard news stories while the STs from both news stories are translated into the TTs. Two time-sensitive events, Hugh Grant's marriage and a U.S. and North Korea summit, were selected. The former (a soft news story) is extracted from the Telegraph and the latter (a hard news story) is from the Washington post. As a result, it was found that such strategies as attitude, engagement, and judgment were used when the source news texts from the hard news story are translated into the target news texts. Under the appraisal theory, the strategies involve evaluative language which refers to positive or negative language that judges the worth of entities. In general, it is said that a journalist frames the SS (especially from the hard news story) to convey his ideology to news consumers. Hypothetically, we assume that a similar framing process takes place in deriving the TT from the SS of the hard news story. Thus, we could conclude that the TT from the hard news story differs from the TT from the soft news story and that the difference can be explained within the framework of White's appraisal theory.

• 음성과학
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• 제3권
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• pp.119-131
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• 1998

We have developed a keyword spotting system for automatic speech editing. This system recognizes the only keyword 'MBC news' and then sends the time information to the host system. We adopted a vocabulary dependent model based on continuous hidden Markov model, and the Viterbi search was used for recognizing the keyword. In recognizing the keyword, the system uses a parallel network where HMM models are connected independently and back-tracking information for reducing false alarms and missing. We especially focused on implementing a stable and practical real-time system.

• 스마트미디어저널
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• 제6권3호
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• pp.41-48
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• 2017

Event detection using social media has been widespread since social network services have been an active communication channel for connecting with others, diffusing news message. Especially, the real-time characteristic of social media has created the opportunity for supporting for real-time applications/systems. Social network such as Twitter is the potential data source to explore useful information by mining messages posted by the user community. This paper proposed a novel system for temporal event detection by analyzing social data. As a result, this information can be used by first responders, decision makers, or news agents to gain insight of the situation. The proposed approach takes advantages of deep learning methods that play core techniques on the main tasks including informative data identifying from a noisy environment and temporal event detection. The former is the responsibility of Convolutional Neural Network model trained from labeled Twitter data. The latter is for event detection supported by Recurrent Neural Network module. We demonstrated our approach and experimental results on the case study of earthquake situations. Our system is more adaptive than other systems used traditional methods since deep learning enables to extract the features of data without spending lots of time constructing feature by hand. This benefit makes our approach adaptive to extend to a new context of practice. Moreover, the proposed system promised to respond to acceptable delay within several minutes that will helpful mean for supporting news channel agents or belief plan in case of disaster events.