• 한국지능시스템학회논문지
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• 제11권7호
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• pp.659-665
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• 2001

Relevance feedback is the most popular query reformulation strategy in a relevance feedback cycle, the user is presented with a list of the retrieved documents and, after examining them, marks those which are relevant. In practice, only the top 10(or 20) ranked documents need to be examined. The main idea consists of selecting important terms, or expressions, attached to the documents that have been identified as relevant by the user, and of enhancing the importance of these terms in a new query formulation. The expected effect is that the new query will be moved towards the relevant documents and away from the non-relevant ones. Local analysis techniques are interesting because they take advantage of the local context provided with the query. In this regard, they seem more appropriate than global analysis techniques. In a local strategy, the documents retrieved for a given query q are examined at query time to determine terms for query expansion. This is similar to a relevance feedback cycle but might be done without assistance from the user.

• International journal of advanced smart convergence
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• 제6권3호
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• pp.29-37
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• 2017

The current behavior recognition system don't match data formats between sensor data measured by user's sensor module or device. Therefore, it is necessary to support data processing, sharing and collaboration services between users and behavior recognition system in order to process sensor data of a large capacity, which is another formats. It is also necessary for real time interaction with users and behavior recognition system. To solve this problem, we propose fog cloud based behavior recognition system for human body sensor data processing. Fog cloud based behavior recognition system solve data standard formats in DbaaS (Database as a System) cloud by servicing fog cloud to solve heterogeneity of sensor data measured in user's sensor module or device. In addition, by placing fog cloud between users and cloud, proximity between users and servers is increased, allowing for real time interaction. Based on this, we propose behavior recognition system for user's behavior recognition and service to observers in collaborative environment. Based on the proposed system, it solves the problem of servers overload due to large sensor data and the inability of real time interaction due to non-proximity between users and servers. This shows the process of delivering behavior recognition services that are consistent and capable of real time interaction.

• Journal of Information Technology Applications and Management
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• 제17권3호
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• pp.1-24
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• 2010

Most of enterprises depend on a data modeler during developing their management information systems. In formulating business requirements for information systems, they widely and naturally use the interview method between a data modeler and a field worker. But, the discrepancy between both parties would certainly cause information loss and distortion that lead to let the systems not faithful to real business works. To improve or avoid modeler-dependant data modeling process, many automated data design CASE tools have been introduced. However, since most of traditional CASE tools just support drawing works for conceptual data design, a data modeler could not generate an ERD faithful to real business works and a user could not use them without any knowledge on database. Although some CASE tools supported conceptual data design, they still required too much preliminary database knowledge for a user. Against these traditional CASE tools, we proposed a Requirement-Oriented Entity Relationship Model for automated data design tool, called ROERM. Based on Non-Stop Methodology, ROERM adopts inner systematic modules for complete and sound ERD that is faithful to real field works, where modules are composed of interaction modules with a user, rules of schema operations and sentence translations. In addition to structure design of ROERM, we also devise detailed algorithms and perform an experiment for a case study.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권1호
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• pp.9-14
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• 2002

Boolean retrieval is simple and elegant. However, since there is no provision for term weighting, no ranking of the answer set is generated. As a result, the size of the output might be too large or too small. Relevance feedback is the most popular query reformulation strategy. in a relevance feedback cycle, the user is presented with a list of the retrieved documents and, after examining them, marks those which are relevant. In practice, only the top 10(or 20) ranked documents need to be examined. The main idea consists of selecting important terms, or expressions, attached to the documents that have been identified as relevant by the user, and of enhancing the importance of these terms in a new query formulation. The expected effect is that the new query will be moved towards the relevant documents and away from the non-relevant ones. Local analysis techniques are interesting because they take advantage of the local context provided with the query. In this regard, they seem more appropriate than global analysis techniques. In a local strategy, the documents retrieved for a given query q are examined at query time to determine terms for query expansion. This is similar to a relevance feedback cycle but might be done without assistance from the user.

• 한국도서관정보학회지
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• 제41권4호
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• pp.127-150
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• 2010

본 연구는 대학도서관 인적 서비스에 대한 대학생들의 인식정도, 신분별 상관성, 전반적인 도서관 만족도와의 영향관계를 검증하고, 품질 인식의 괴리 원인 분석과 개선안을 제시하고자 한다. 인식도의 분석결과, 이용자의 현행서비스에 대한 인식은 아주 낮고, 서비스 품질은 최소한의 수준에도 미치지 못하였다. 품질 요인에서 희망수준이 높은 것은 미소장자료의 신속한 입수와 공손함이었고, 희망수준과 괴리가 큰 요인은 충분한 주제전문서비스와 자발적인 도움이었다. 서비스 품질은 도서관 만족도에 영향을 주었으며, 주제전문서비스, 이용자 요구의 정확한 이해, 예의바르고 공손함이 영향을 많이 주었다. 인식 괴리 원인은 사서들의 무관심, 질문응답의 의욕부족, 커뮤니케이션의 부족, 이용자에 대한 배려 부족 등이었다.

• Management Science and Financial Engineering
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• 제15권1호
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• pp.51-69
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• 2009

A network model and a Genetic Algorithm (GA) is proposed to solve the simultaneous estimation of the trip distribution and traffic assignment from traffic counts in the congested networks in a logit-based Stochastic User Equilibrium (SUE). The model is formulated as a problem of minimizing a non-linear objective function with the linear constraints. In the model, the flow-conservation constraints are utilized to restrict the solution space and to force the link flows become consistent to the traffic counts. The objective of the model is to minimize the discrepancies between two sets of link flows. One is the set of link flows satisfying the constraints of flow-conservation, trip production from origin, trip attraction to destination and traffic counts at observed links. The other is the set of link flows those are estimated through the trip distribution and traffic assignment using the path flow estimator in the logit-based SUE. In the proposed GA, a chromosome is defined as a real vector representing a set of Origin-Destination Matrix (ODM), link flows and route-choice dispersion coefficient. Each chromosome is evaluated by the corresponding discrepancies. The population of the chromosome is evolved by the concurrent simplex crossover and random mutation. To maintain the feasibility of solutions, a bounded vector shipment technique is used during the crossover and mutation.

• 대한가정학회지
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• 제43권11호
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• pp.1-15
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• 2005

The purpose of this study was to investigate the attitude, knowledge and need for educational contents about credit cards according to credit card use, and to examine the status of credit card use and the factors affecting credit card management behaviors of college students. The data were collected from 481 college students in Busan and Kyungnam areas by a self-administered questionnaire. Frequencies, Cronbach's alpha, factor analysis, t-test, ${\chi}^2$ analysis, Pearson's correlation analysis and regression analyses were conducted by SPSS WINDOWS. The results from this study were as follows. First, there were no significant differences between the credit card user group and the non-user group in the means of their altitude and knowledge towards credit cards. The mean of each category of the need for educational contents was high in both groups. Second, respondents of the credit card user group answered that they used credit cards whenever necessary, using them to purchase mostly clothing, shoes, and books. Third, credit card management behaviors were influenced by the allowance amount, experience of consumer education related to credit cards, number of total credit cards, attitude towards credit cards, knowledge about credit cards, frequency of credit card use, terms of credit card use and father's occupation. These results suggest that consumer education should be conducted for the credit card management behaviors of college students.

• 한국인터넷방송통신학회논문지
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• 제9권4호
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• pp.123-127
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• 2009

Cognitive Radio 환경에서 서비스영역 밖에 있는 사용자는 통신을 하지 못하도록 규정을 하고 있다. 그 이유는 주사용자가 서비스를 제공받는데 피해나 간섭의 영향을 대비하기 위해서이다. 이와 같은 규정이 보장된다면, CR 사용자는 서비스 영역 밖에서도 충분히 서비스를 제공받을 수 있게 된다. 본 논문에서는 주 사용자에게 과도한 간섭을 발생시키지 않는 실용적 시스템에 대한 논의, 즉, 제안된 기법을 통해 부사용자를 위한 가능한 이득이 주사용자에게 비간섭이 되는 사항에 중점을 둔다. 본 논문에서는 그 방법을 BBA(Bi-directional Beamforming Antenna), 즉 지향성 양방향 안테나를 이용하여 제시한다.

• 융합보안논문지
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• 제7권4호
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• pp.123-131
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• 2007

최근 각종 보안 침해 사고는 불특정 다수를 대상으로 발생하고 있으며, 이는 네트워크를 통한 정보의 공유가 가속화되면서 그 피해가 더욱 늘어나고 있다. 이러한 보안 침해 사고는 침입차단시스템, 침입탐지시스템, 가상사설망 등 정보보호시스템의 활용으로 최소화가 가능하지만, 이는 전문가적인 지식이 필요하며 일반 사용자가 운영하기가 쉽지 않다. 본 논문에서는 일반 사용자가 쉽게 사용할 수 있도록 파일 접근 제어 모듈을 설계 및 개발하였고, 이는 공격에 대한 탐지가 아닌 운영체제상에서 공격에 대한 차단할 수 있다. 본 논문에서 구현한 파일 접근 제어 모듈은 윈도우환경 뿐만 아니라 리눅스 환경에서도 적용할 수 있으며, 다중 사용자가 사용하는 운영체제에 따라 파일에 대한 접근 제어를 함으로써 파일에 대한 접근제어, 무결성, 부인 방지를 할 수 있다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권3호
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• pp.175-184
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• 2008

To construct user profiles automatically, an extraction method for representative keywords from a set of documents is needed. In our previous works, we suggested such a method and showed its usefulness. Here, we apply it to the classification problem and observe how much it contributes to performance improvement. The method can be used as a linear document classifier with few modifications. So, we first evaluate its performance for that case. The method is also applicable to some non-linear classification methods such as GIS (Generalized Instance Set). In GIS algorithm, generalized instances are built from training documents by a generalization function and then the K-NN algorithm is applied to them, where the method can be used as a generalization function. For comparative works, two famous linear classification methods, Rocchio and Widrow-Hoff algorithms, are also used. Experimental results show that our method is better than the others for the case that only positive documents are considered, but not when negative documents are considered together.