• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권2호
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• pp.122-129
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• 2014

Effective information gathering and retrieval of the most relevant web documents on the topic of interest is difficult due to the large amount of information that exists in various formats. Current information gathering and retrieval techniques are unable to exploit semantic knowledge within documents in the "big data" environment; therefore, they cannot provide precise answers to specific questions. Existing commercial big data analytic platforms are restricted to a single data type; moreover, different big data analytic platforms are effective at processing different data types. Therefore, the development of a common big data platform that is suitable for efficiently processing various data types is needed. Furthermore, users often possess more than one intelligent device. It is therefore important to find an efficient preference profile construction approach to record the user context and personalized applications. In this way, user needs can be tailored according to the user's dynamic interests by tracking all devices owned by the user.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2000년도 춘계정기학술대회 e-Business를 위한 지능형 정보기술 / 한국지능정보시스템학회
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• pp.145-155
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• 2000

• 정보처리학회논문지B
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• 제13B권4호
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• pp.421-428
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• 2006

Intelligent Tutoring System(ITS)이 다양한 학습자 변인을 고려한 개별화된 학습 환경을 제공하여 영역 전문가를 대신할 효율적인 대안으로 인식되어짐에 따라, Learning Companion System(LCS)에 대한 연구도 긍정적으로 검토되어지고 있다. 하지만 LCS에서의 원활한 상호작용을 위해서는 동일한 역할을 하는 복수 LC의 결합이 필요하고, 이는 개별적 지식베이스의 확보를 선행 조건으로 요구한다. 따라서 본 연구에서는 인지구조의 연결주의적 관점을 근거로, 지식베이스 자체의 자기 학습(self learning)이 가능하고, 지식베이스 객체의 소유자에 의해 적응적으로 성장 가능한 지식베이스 객체 모형을 설계하고, 이를 검증하였다. 이 지식베이스 객체 모형은 개별적 지식베이스의 구축을 가능하게 하여, 지식베이스 객체를 이용한 적응적 ITS 개발의 기회를 제공한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권2호
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• pp.215-221
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• 2003

Generally, we want to be searched the newest as well as some appropriate personalized information from the internet resources. However, it is a complex and repeated procedure to search some appropriate information. Moreover, because the user's interests are changed as time goes, the real time modeling of a user's interests should be necessary. In this paper, I propose PREA system that can search and filter documents that users are interested from the World Wide Web. And then it constructs the user's interest model by a modified spreading neural network. Based on this network, PREA can easily produce some queries to search web documents, and it ranks them. The conventional spreading neural network does not have a visualization function, so that the users could not know how to be configured his or her interest model by the network. To solve this problem, PREA gives a visualization function being shown how to be made his interest user model to many users.

• 방송공학회논문지
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• 제15권5호
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• pp.632-641
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• 2010

본 논문은 양방향 개인 맞춤형 방송 시스템 구축에 관한 연구이다. 맞춤형 방송이란 사용자가 원하는 방송 프로그램만을 사용자가 원하는 시간에 볼 수 있게 하는 서비스를 말한다. 양방향 방송 서비스는 사용자의 방송단말과 방송 서버 사이의 양방향 데이터 전송을 허용하여 만족도 높고 개인화된 방송 서비스를 제공하는 것을 목표로 한다. 본 연구는 양방향 맞춤형 방송 서비스를 위한 사용자 프로파일 시스템을 개발하였다. 이 시스템은 맞춤형 방송 서비스를 위한 표준인 TV-Anytime에서 제안하고 있는 메타데이터를 기반으로 사용자 프로파일과 콘텐츠 데이터 및 맞춤형 광고 서비스를 포함한 맞춤형 방송의 다양한 기능을 포함하여 양방향 데이터 전송까지 지원하고 있다. 구축된 양방향 맞춤형 방송 시스템은 사용자 프로파일을 통하여 개인 별로 선호하는 방송 콘텐츠 및 광고를 추천 및 지원하여 사용자의 시청 만족도를 높였으며, 기존의 방송과 차별화된 지능적인 방송 서비스의 지원으로 사용자의 만족도를 증가시켰다.

• 한국멀티미디어학회논문지
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• 제21권2호
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• pp.224-231
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• 2018

Recently, the importance of intelligent personalized services is increasing in the era of the 4th Industrial Revolution. In this paper, we proposes design and implementation of the agent recruitment service system for the intelligent headhunting service. The proposed service system has designed and implemented an intelligent service system to efficiently recruit and manage applicants(job seekers). In addition, we develops the modules that can analyze the profile information of the applicant(job seeker), and implement the algorithm to predict the talent verification and analyze the talent type. The proposed service system is expected to contribute to designing the innovative and new service models for the intelligent agent recruitment service system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권1호
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• pp.21-26
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• 2006

In this paper, we propose a customer personalized system that presents the web pages to users which are customized to their individuality. It analyzes the action of users who visit the shopping mall, and preferentially supplies the necessary information to them. When they actually buy some items, it forecasts the user's access pattern to web site and their following purchasable items and improves their web page on the bases of their individuality. It reasons the relation among the web documents and among the items by using the log data of web server and the purchase information of DB. For reasoning, it employs Apriori algorithm, which is a method that searches the association rule. It reasons the web pages by considering the user's access pattern and time by using the web log and reasons the user's purchase pattern by using the purchase information of DB. On the basis of the relation among them, it appends the related web pages to link of user's web pages and displays the inferred goods on user's web pages.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2006년도 추계학술대회 학술발표 논문집 제16권 제2호
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• pp.29-32
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• 2006

In this paper, we propose a customer personalized system that presents the web pages to users which are customized to their individuality. It analyzes the action of users who visit the shopping mall, and preferentially supplies the necessary information to them. When they actually buy some items, it forecasts the users' access pattern to web site and their following purchasable items and improves their web pare on the bases of their individuality. It reasons the relation among the web documents and among the items by using the log data of web server and the purchase information of DB. For reasoning it employs Rough Set, which is a method that searches the association rule and offers most suitable cases by reduces cases. It reasons the web pages by considering the users' access pattern and time by using the web log and reasons the users' purchase pattern by using the purchase information of DB. On the basis of the relation among them, it appends the related web pages to link of users' web pages and displays the inferred goods on users' web pages.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2005년도 공동추계학술대회
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• pp.359-368
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• 2005

Personalized reminder systems have to identify the user's current needs dynamically and proactively based on the user's current context. However, need identification methodologies and their feasible architectures for personalized reminder systems have been so far rare. Hence, this paper aims to propose a proactive need awaring mechanism by applying agent, semantic web technologies and RFID-based context subsystem for a personalized reminder system, which is one of the supporting systems for a robust ubiquitous service support environment. Rescorla-Wagner model is adopted as an underlying need awaring theory. We have created a prototype system. called NAMA(Need Aware Muiti-Agent)-RFID. to demonstrate the feasibility of the methodology and of the mobile settings framework that we propose in this paper Moreover, to test if the proposed system works in terms of scalability, a simulation was performed and the results are described.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
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• pp.153-156
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• 2005

본 논문에서는 협상에이전트를 기반으로 모바일 환경에서 개인 디지털 라이브러리 시스템을 구축하는 것에 관한 것을 연구하였다. 시스템 구축 실험결과 단일 에이전트를 사용한 것보다 멀티에이전트에서 협상에이전트를 사용한 것이 보다 높은 효율성을 보여주었음을 알 수 있었다.