• Annual Conference of KIPS
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• 2023.05a
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• pp.698-700
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• 2023

본 논문에서는 한국어 데이터와 모델링, 추가 평가 지표를 통해 Text Summarization 분야에서 한국어로 좋은 성능을 내기 위한 방식을 제안한다. KoBART의 크기를 키우고 PEGASUS의 GSG를 사용하는 KoBART-GSG 모델을 제안한다. 이때 ASR 모델을 사용하여 한국어 데이터를 구축하고 추가 학습을 진행한다. 또한, 생성된 요약문과 원문에서 Attention 기법으로 키워드와 핵심 문장을 추출하여 지능형 텍스트를 구성하는 새로운 방식을 제안한다. ASR Open API와 제안한 방식을 사용하여 오디오 파일을 텍스트로 변환하고 요약하는 강의나 회의 등 학계와 산업에서 사용할 수 있는 서비스를 제공한다.

• Annual Conference of KIPS
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• 2023.11a
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• pp.345-346
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• 2023

지난 몇 년간 온라인 쇼핑 시장은 크게 성장하고 있다. 쇼핑몰에서 제공하는 최저 가격 정렬 기능은 사용자에게 편의성을 제공하나 배송비 포함이 제각각임에 따라 실질적인 최저 가격 정렬이 불가능하다는 한계가 있다. 본 연구에서는 배송비가 적용된 가격으로 보여주는 프로그램을 제안하고자 한다. 제안 프로그램은 크롬 확장 프로그램으로 구현되며 Open API와 스크롤링을 통해 획득한 배송비 정보까지 포함된 최종가격 정보를 제공한다. 이를 통해 배송비가 포함된 실질적인 가격 비교 정보를 제공하여 사용자 편의성을 크게 향상 시킬 것으로 기대된다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.177-183
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• 2015

The purpose of ICT Healing platform is the prevention of chronic disease. It is intended to early warning of the disease through the information such as the bio-signals and lifestyle. In this paper, we provide a 2-Step open system(TOS) for personalized health data access. TOS is connected between the personal health related data providers and service providers of individuals ICT Healing platform, a software engine for relaying personalized health data. The proposed system, to operate in isolation to 2 step in personal health document repository Inbound module and Outbound module to provide an inquiry service to external organizations. Therefore, we propose a personalized editable Manifest concept for defining data exchange between Step. This can be used as a reference model to collect the personal health information is scattered in many health related service institutions (Hospitals, Fitness Centers, Health Examination Centers, Personal Health Device, etc.) and under private-led liberalization.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.152-155
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• 2010

IP기반 미디어 서비스는 대규모 사용자를 확보할 수 있고, 사용자 규모에 따른 수익을 올릴 수 있기 때문에 방송사에서는 중요 서비스의 하나로 인식하고 있다. 사용자의 지속적이고 빠르게 변화하는 새로운 서비스에 대한 요구사항들을 만족시키기 위해서 방송사는 보유하고 있는 관련 시스템들을 항시 새로운 서비스에 유연하게 대처할 수 있도록 해야 한다. 본 논문에서는 IP기반 미디어 서비스에 유연하게 대응할 수 있는 체계화된 방송콘텐츠 서비스 개방형 아키텍처 (OASIS: Open Architecture for Systematic IP-based Services)를 제안한다. 'OASIS'는 제작 시스템에서 자동으로 콘텐츠(예. 에센스와 메타데이터)를 수집하고 다양한 서비스에 맞게 수집된 콘텐츠를 제공할 수 있는 체계적이고 유연한 아키텍처이다. 더불어 OASIS는 방송콘텐츠 저작권 확보 여부를 확인할 수 있도록 하였기 때문에 최근 중요시되고 있는 저작권이 확보된 콘텐츠를 서비스할 수 있다. 제안하는 아키텍처는 시스템들 간에 콘텐츠를 교환할 때 표준화된 메타데이터와 ID를 사용하여 교환하게 함으로써 서비스 할 콘텐츠를 자동으로 시스템화하여 수집할 수 있다. KBS는 2년간의 작업을 거쳐 방송콘텐츠를 공유하는 데 필요한 메타데이터와 ID의 표준화 작업을 수행하였으며, 이를 기반으로 체계적으로 자동화된 수집 체계를 고안하였다. 다양한 서비스에 유연하게 콘텐츠를 제공하기 위한 측면으로는 openAPI(Application Programming Interface)를 활용하여, 서비스의 요구에 맞는 콘텐츠 내용을 제공할 수 있도록 하였다. 마지막으로 라이선스 관리 측면으로는 방송 콘텐츠 제작 시 수집할 수 있는 계약 정보 및 서비스 유통 가능 범위를 체계화함으로써, 제작 시에 저작권 정보를 수집하고, 해당 콘텐츠와 연동하여 서비스 가능 여부를 확인할 수 있도록 하였다. 제안한 아키텍처를 활용하여 다양한 서비스의 요구에 대응할 수 있는 콘텐츠 서비스 시스템을 구축할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2101-2121
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• 2020

The rapid growth of instructional videos repositories and their widespread use as a tool to support education have raised the need of studies to assess the quality of those educational resources and their impact on the quality of learning process that depends on them. Khan Academy (KA) repository is one of the prominent educational videos' repositories. It is famous and widely used by different types of learners, students and teachers. To better understand its characteristics and the impact of such repositories on education, we gathered a huge amount of KA data using its API and different web scraping techniques, then we analyzed them. This paper reports the first quantitative and descriptive analysis of Khan Academy repository (KA repository) of open video lessons. First, we described the structure of repository. Then, we demonstrated some analyses highlighting content-based growth and evolution. Those descriptive analyses spotted the main important findings in KA repository. Finally, we focused on users' interactions with video lessons. Those interactions consisted of questions and answers posted on videos. We developed interaction profiles for those videos based on the number of users' interactions. We conducted regression analysis and statistical tests to mine the relation between those profiles and some quality related proposed metrics. The results of analysis showed that all interaction profiles are highly affected by video length and reuse rate in different subjects. We believe that our study demonstrated in this paper provides valuable information in understanding the logic and the learning mechanism inside learning repositories, which can have major impacts on the education field in general, and particularly on the informal learning process and the instructional design process. This study can be considered as one of the first quantitative studies to shed the light on Khan Academy as an open educational resources (OER) repository. The results presented in this paper are crucial in understanding KA videos repository, its characteristics and its impact on education.

• Journal of the Korea Society of Computer and Information
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• v.26 no.8
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• pp.39-46
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• 2021

When conducting social big data analysis for franchise stores, reviews of multiple branches of a franchise can be collected together, from which analysis results can be distorted significantly. To improve its accuracy, it should be possible to filter reviews of other branches properly which are not subject to the analysis. This paper presents a method for social big data analysis which reflects characteristics of franchise stores. The proposed method consists of search key configuration and review filtering. For the former, the open data provided by Small Business Promotion Agency is used to extract region names for collecting reviews more accurately. For the latter, open search APIs provided by Naver or Kakao are used to obtain franchise branch information for filtering reviews of other branches that are not subject to analysis. To verify performance of the proposed method, experiments were conducted based on real social reviews collected from online, where the results showed that the accuracy of the proposed review filtering was 93.6% on the average.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2305-2311
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• 2017

In recent years, there have been tries to open public data from various government agencies along with publicization of public information for the public interest. In other words, various kinds of electronic data generated and collected by the public institutions as a result of their work are opened in the public portal sites. However, users who use it are limited in their use of big data due to lack of understanding of data format, lack of data processing knowledge, difficulty in accessing and managing data, and lack of visualization data to understand collected and stored data. Therefore, in this study, we propose a big data collection, storing and visualization platform that can collect big data provided by various public sites using data set URL and API regardless of data format, re-process collected data using XML structure.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.3
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• pp.95-104
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• 2012

The companies have employed SNS for marketing, promotion, and customer relationship management. The SNS is a good tool to collect customers' opinions and to collaborate with internal and external employees, however, the function of SNS are limited in implementing a co-creation. Therefore, the purpose of this research is to suggest a SNS platform for co-creation that creates a corporate's values with customers. For this purpose, the limitations of SNS are defined and the new platform of the SNS is suggested. The proposed platform has 3 modules including integration of applications, cloud services, and integration to applications operated by companies. With a scenario method the suggested platform was validated. This is one of pioneer studies in co-creation.

• Journal of Broadcast Engineering
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• v.15 no.4
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• pp.540-546
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• 2010

Since the stereoscopic 3-dimensional (3D) video that provides users with a realistic multimedia service requires twice as much data as 2-dimensional (2D) video, it is difficult to construct the fast system. In this paper, we propose a fast stereoscopic 3D broadcasting system based on the depth information. Before the transmission, we encode the input 2D+depth video using x264, an open source H.264/AVC fast encoder to reduce the size of the data. At the receiver, we decode the transmitted bitstream in real time using a compute unified device architecture (CUDA) video decoder API on NVIDIA graphics processing unit (GPU). Then, we apply a fast view synthesis method that generates the virtual view using GPU. The proposed system can display the output video in both 2DTV and 3DTV. From the experiment, we verified that the proposed system can service the stereoscopic 3D contents in 24 frames per second at most.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.4
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• pp.709-719
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• 2015

This paper introduces a proper renaming service using variable action and security services against the analysis techniques in Java code. The renaming service that is introduced is separated into API pattern and loop condition. We present our scheme algorithm with known Java obfuscation techniques and tools in order to help readers understanding, and implement prototype to prove practicality in this paper. Test result using prototype shows 73% successful variable renaming rate. Using our scheme, cooperators can intuitionally understand all of code. Also, It helps malware analysts to predict malware action by variable name. But application source code that is developed by Java is exposed to hackers easily using our scheme. So we introduce Java application code protection methods, too.