• Journal of the Korean Society for information Management
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• v.26 no.1
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• pp.81-105
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• 2009

In this paper, we propose user contents using behavior and location information on contents on various channels, such as web, IPTV, for contents distribution. With methods to build user and contents profiles, contents using behavior as an implicit user feedback was applied into machine learning procedure for updating user profiles and contents preference. In machine learning procedure, contents-based and collaborative filtering methods were used to analyze user's contents preference. This study proposes contents location information on web sites for final recommendation contents as well. Finally, we refer to a generalized recommender system for personalization. With those methods, more effective and accurate recommendation service can be possible.

• Journal of the Korean Society for information Management
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• v.26 no.4
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• pp.113-128
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• 2009

Generally, a user uses briefly summarized video data and text information to search video contents. To provide fast and accurate search tool for video contents in the process of searching video contents, this study proposes a method to search video clips which was partitioned from video contents. To manage and control video contents and metadata, the proposed method creates structural information based on XML on a video and metadata, and saves the information into XML database. With the saved information, when a user try to search video contents, the results of user's query to retrieve video contents would be provided through creating Xpath which has class structure information. Based on the proposed method, an information retrieval system for video clips was designed and implemented.

• Journal of the Korean Society for information Management
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• v.24 no.2
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• pp.89-104
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• 2007

This research attempts to give a personalized recommendation framework in large-sized music contents environment. Despite of existing studios and commercial contents for recommendation systems, large online shopping malls are still looking for a recommendation system that can serve personalized recommendation and handle large data in real-time. This research utilizes data mining technologies and new pattern matching algorithm. A clustering technique is used to get dynamic user segmentations using user preference to contents categories. Then a sequential pattern mining technique is used to extract contents access patterns in the user segmentations. And the recommendation is given by our recommendation algorithm using user contents preference history and contents access patterns of the segment. In the framework, preprocessing and data transformation and transition are implemented on DBMS. The proposed system is implemented to show that the framework is feasible. In the experiment using real-world large data, personalized recommendation is given in almost real-time and shows acceptable correctness.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.720-725
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• 2009

SDI(Selective Dissemination of Information) is on demand service to inform to the user applies a service after inputting a search strategy, when new information is obtained. This Paper propose the ways to develope the dynamic RSS channel generator for supporting SDI service. The RSS which is a kind of syndication technology enables a part or the whole of the content which it provides from web site to be able to be used in different service. It is protocol to summarize and share various contents on web site. Also, the users register the channel RSS to the RSS aggregator system and recommend it. It can drive to share of knowledge between researchers.

• Proceedings of the Korea Contents Association Conference
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• 2017.05a
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• pp.421-422
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• 2017

콘텐츠 큐레이션 서비스를 위해서 대용량 데이터를 학습하는 과정에서 발생하는 메모리부족 문제, 학습소요시간 문제 등을 해결하기 위한 "대용량 문서학습을 위한 동적학습 파이프라인 생성기술 중 빅데이터 마이닝을 위한 점진적 학습 모델" 기술이 필요하며, 본 논문에서 제안한 콘텐츠 큐레이션 서비스는 온라인상의 수많은 콘텐츠들 중 개인의 주관이나 관점에 따라 관련 콘텐츠들을 수집, 정리하고 편집하여 이용자와 관련이 있거나 좋아할 만한 콘텐츠를 제공하는 서비스이다. 큐레이션 서비스에서는 개인비서, 금융 분야의 투자, 자율주행, 저널리즘, 효율적인 업무 지시/감독, 제조업의 자동화 공정, 교육, 콘텐츠 유통, 학술정보 등에서 컴퓨터가 방대한 양의 데이터로 부터 학습하여 사람의 일을 대신 처리하거나 의사결정에 도움을 줌으로써 업무의 효율을 높여주는 서비스 산업에 활용이 가능하다.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.401-402
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• 2018

콘텐츠 큐레이션 서비스를 위해서 대용량 데이터를 학습하는 과정에서 발생하는 메모리부족 문제, 학습소요시간 문제 등을 해결하기 위한 "대용량 문서학습을 위한 동적학습 파이프라인 생성기술 중 빅데이터 마이닝을 위한 점진적 학습 모델" 기술이 필요하며, 본 논문에서 제안한 콘텐츠 큐레이션 서비스는 온라인상의 수많은 콘텐츠들 중 개인의 주관이나 관점에 따라 관련 콘텐츠들을 수집, 정리하고 편집하여 이용자와 관련이 있거나 좋아할 만한 콘텐츠를 제공하는 서비스이다. 본 논문에서 설계된 모아 큐레이션 서비스는 대용량의 문서를 학습함에 있어서 메모리 부족 문제, 학습 소요시간 문제 등을 해결하기 위해 학습데이터의 용량 제한이 없는 문서를 자유롭게 학습하고 부분적인 자질추가/변경 시에 변경요소만을 추가 반영할 수 있는 범용적이고 일반적인 분류기의 구조설계 방법 등을 제시하였다.

• The KIPS Transactions:PartD
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• v.19D no.4
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• pp.271-280
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• 2012

Currently, contents generated by SNS services are increasing exponentially, as the number of SNS users increase. The SNS is commonly used to post personal status and individual interests. Also, the SNS is applied in socialization, entertainment, product marketing, news sharing, and single person journalism. As SNS services became available on smart phones, the users of SNS services can generate and spread the social issues and controversies faster than the traditional media. The existing indexing methods for web contents have limitation in terms of real-time indexing for SNS contents, as they usually focus on diversity and accuracy of indexing. To overcome this problem, there are real-time indexing techniques based on RDBMSs. However, these techniques suffer from complex indexing procedures and reduced indexing targets. In this regard, we introduce the TK-Indexing method to improve the previous indexing techniques. Our method indexes the generation time of SNS contents and keywords by way of NoSQL to indexing SNS contents in real-time.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1007-1015
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• 2013

The automatic payment process of mobile phone micropayment system has not checked user's authentication. That is the structural vulnerability of mobile phone micropayment system. The malicious contents provider can cheat users and payment gateway through abusing the structural vulnerability. The payment gateway applies standard payment module after August, 2012 in order to solve the problem. But the standard payment module also has the vulnerability that makes damage of users. So the purpose of this paper is to suggest efficient improvement of standard payment module for user protection.

• Electronics and Telecommunications Trends
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• v.17 no.6 s.78
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• pp.193-203
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• 2002

본 고에서는 인터넷 기반에서 디지털 콘텐츠 유료화를 위한 정보거래시스템의 구현을 목표로 디지털 콘텐츠 유료화에 관한 최신의 기술 동향 및 실제적인 시스템 구현을 위한 구성 요소들을 살펴 보고자 한다. 이에 디지털 콘텐츠 유료화를 위해서 반드시 필요되는 디지털 콘텐츠 보안 기술, 과금(빌링)시스템, 전자 결제 방식 및 PG, 디지털 콘텐츠 전송기술, 디지털 콘텐츠 저작권 보호 기술 등에 대한 내용 중심으로 고찰할 것이다. 또한 이를 기반으로 구현하고자 하는 정보거래시스템의 커머스 모델로는 C-to-C 개념으로 인터넷 기반의 정보 생성자와 정보 이용자를 직접 연계하고, 정보 이용에 대한 지불 처리가 가능하도록 하여 기존의 C-to-B 및 B-to-B 기반 전자상거래에서 C-to-C 기반 전자상거래 개념 도입을 통한 정보거래 기반 및 정보 자체에 대한 인터넷 거래 활성화를 유도할 수 있는 기술적 기반 환경을 조성하고, 실제적으로 활용이 가능한 프로토타입 모델을 설계하고자 한다.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.23 no.4
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• pp.283-308
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• 2012

With explosive growth of information by recent advancements in information technology and the Internet, users need a method to acquire appropriate information. To solve this problem, an information retrieval and filtering system was developed as an important tool for users. Also, users and service providers are growing more and more interested in personalized information recommendation. This study designed and implemented personalized information recommendation system based on AR as a method to provide positive information service for information users as a method to provide positive information service. To achieve the goal, the proposed method overcomes the weaknesses of existing systems, by providing a personalized recommendation method for contents that works in a large-scaled data and user environment. This study based on the proposed method to extract rules from log files showing users' behavior provides an effective framework to extract Association Rule.