• 한국지능시스템학회논문지
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• 제11권5호
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• pp.441-447
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• 2001

In general, Rough Set theory is used for classification, inference, and decision analysis of incomplete data by using approximation space concepts in information system. Information system can include quantitative attribute values which have interval characteristics, or incomplete data such as multiple or unknown(missing) data. These incomplete data cause tole inconsistency in information system and decrease the classification ability in system using Rough Sets. In this paper, we present various types of incomplete data which may occur in information system and propose INcomplete information Processing System(INiPS) which converts incomplete information system into complete information system in using Rough Sets.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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• pp.243-251
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• 2000

In general, Rough Set theory is used for classification, inference, and decision analysis of incomplete data by using approximation space concepts in information system. Information system can include quantitative attribute values which have interval characteristics, or incomplete data such as multiple or unknown(missing) data. These incomplete data cause the inconsistency in information system and decrease the classification ability in system using Rough Sets. In this paper, we present various types of incomplete data which may occur in information system and propose INcomplete information Processing System(INiPS) which converts incomplete information system into complete information system in using Rough Sets.

• 한국멀티미디어학회논문지
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• 제3권5호
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• pp.550-556
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• 2000

러프집합에서는 식별불능관계와 근사공간 개념을 이용해서 불완전 정보로부터 최적화된 결정규칙을 유도하게 된다. 그러나, 처리 하고자 하는 정보에 정량적이거나 중복 또는 누락된 데이터가 포함된 경우에는 오류가 발생될 수 있으므로, 이러한 데이터들을 제거하거나 최소화시키는 방법이 필요하다. 정보처리 분야에서 불확실성이나 정보의 양을 측정하는데 사용되고 있는 엔트로피는 러프 관계 데이터베이스의 불완전 정보를 제거하는데 사용되었다. 그러나, 정보시스템에 포함될 수 있는 불완전 정보를 모두 다루지는 못하였다. 본 논문에서는 정보시스템의 조건속성과 결정속성에 포함될 수 있는 불완전 정보를 제거하기 위한 정보 이론적 척도로서 러프집합을 이용한 객체관계 엔트로피와 속성관계 엔트로피를 제시한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 A
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• pp.778-780
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• 2005

Electric power industry throughout the world is restructured. The electric power industry has a characteristics of an oligopoly with an imperfect competition. In Korea rules, all information is not available. So the strategy under such incomplete information market differ firm those under complete information system in game theory. This paper presents a analysis technique if Korea ma rket model with incomplete information.

• 지능정보연구
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• 제9권2호
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• pp.51-63
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• 2003

Collaborative filtering is one of the methodologies that are most widely used for recommendation system. It is based on a data matrix of each customer's preferences of products. There could be a lot of missing values in such preference data matrix. This incomplete data is one of the reasons to deteriorate the accuracy of recommendation system. There are several treatments to deal with the incomplete data problem such as case deletion and single imputation. Those approaches are simple and easy to implement but they may provide biased results. Multiple imputation method imputes m values for each missing value. It overcomes flaws of single imputation approaches through considering the uncertainty of missing values. The objective of this paper is to suggest multiple imputation-based collaborative filtering approach for recommendation system to improve the accuracy in prediction performance. The experimental works show that the proposed approach provides better performance than the traditional Collaborative filtering approach, especially in case that there are a lot of missing values in dataset used for recommendation system.

• International Journal of Advanced Culture Technology
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• 제7권3호
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• pp.92-96
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• 2019

This study analyzes the problems of fire qualification information websites and job search websites due to incomplete information in the job search process and suggests an improvement plan. It has been confirmed that the main reason for the cost of job searching is incomplete information required for a job search and job search through existing analysis. As a result, it is suggested to construct a smooth information system for economic entities and to provide easy access to information by mitigating the incompleteness of information. Based on this, analysis of the problems of Korean qualifications in the firefighting realm reveals that there is a qualification holder information and a job information site, and a qualification holder management system is established but only information of either qualification acquisition information or employment information is provided. In addition, it is easy to access information through a qualification acquisition information and employment information site via the Internet, but there are inconveniences that qualification acquisition information and employment information are dualized. In order to improve this, it is necessary to build a new customized integrated qualification management system that covers existing Q-net qualification acquisition information and worknet employment information.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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• pp.281-287
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• 1999

Decision class analysis (DCA) is viewed as a classification problem where a set of input data (situation-specific knowledge) and output data(a topological leveled influence diagram (ID)) is given. Situation-specific knowledge is usually given from a decision maker (DM) with the help of domain expert(s). But it is not easy for the DM to know the situation-specific knowledge of decision problem exactly. This paper presents a methodology for sensitivity analysis of DCA under incomplete information. The purpose of sensitivity analysis in DCA is to identify the effects of incomplete situation-specific frames whose uncertainty affects the importance of each variable in the resulting model. For such a purpose, our suggested methodology consists of two procedures: generative procedure and adaptive procedure. An interactive procedure is also suggested based the sensitivity analysis to build a well-formed ID. These procedures are formally explained and illustrated with a raw material purchasing problem.

• 전자공학회논문지
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• 제50권5호
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• pp.121-127
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• 2013

작은 입력신호의 spectral-amplitude-code(SAC) optical code-division multiple-access (OCDMA) 시스템에는 nonideal symmetric balance incomplete block design(BIBD) code의 사용이 효율적이나 충분한 사용자를 수용하지 못하는 단점이 있다. 이를 극복하기 위하여 본 논문에서는 ideal BIBD code를 공간 코드로 사용하고 nonideal code를 파장 코드로 사용하는 two-dimensional(2-D) BIBD code를 제안한다. 사용자 수에 따른 bit error-rate(BER) 분석을 통하여 제안하는 2-D BIBD code가 1-D BIBD code에 비하여 최대사용자 수를 현저하게 증가시킬 수 있음을 알 수 있다.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.105-110
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• 2003

Collaborative filtering is one of the methodologies that are most widely used for recommendation system. It is based on a data matrix of each customer's preferences of products. There could be a lot of missing values in such preference. data matrix. This incomplete data is one of the reasons to deteriorate the accuracy of recommendation system. Multiple imputation method imputes m values for each missing value. It overcomes flaws of single imputation approaches through considering the uncertainty of missing values.. The objective of this paper is to suggest multiple imputation-based collaborative filtering approach for recommendation system to improve the accuracy in prediction performance. The experimental works show that the proposed approach provides better performance than the traditional Collaborative filtering approach, especially in case that there are a lot of missing values in dataset used for recommendation system.

• 정보처리학회논문지C
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• 제18C권3호
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• pp.127-134
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• 2011

악성 봇넷은 DDoS(Distributed Denial of Service) 공격이나 각종 스팸 메시지 발송, 개인 정보 탈취, 클릭 사기 등 많은 악성 행위에 이용되고 있다. 이를 방지하기 위해 많은 연구가 선행되었지만 악성 봇넷 또한 진화하여 탐지 시스템을 회피하고 있다. 특히 최근에는 어플리케이션 계층의 취약성을 공략한 HTTP GET 공격이 주로 사용되고 있다. 한국전자통신연구원에서 개발한 ALADDIN 시스템의 ALAB(Application Layer Attack detection Block)는 서비스 거부 공격 HTTP GET, Incomplete GET Request flooding 공격을 탐지하는 알고리즘이 적용된 탐지 시스템이다. 본 논문에서는 ALAB 탐지 알고리즘의 Incomplete GET 탐지 알고리즘을 확장하고 장기간 조사한 정상적인 패킷 및 공격 패킷들의 분석을 통해 최적 threshold를 도출하여 ALAB 알고리즘의 유효성을 검증한다.