• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.391-396
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• 2008

유비쿼터스 컴퓨팅의 목표 중 하나는 사용자의 직접적이거나 은연중에 내포된 요청에 따라 적절한 서비스를 제공하는 것이다. 최근에는 사용자의 다양한 요청에 보다 유연하게 대응할 수 있는 연구가 이루어지고 있으며 그 중 단일서비스의 조합을 통해 복합서비스를 제공할 수 있는 서비스 컴포지션(Service Composition)이 주목을 받고 있다. 하지만 기존 연구들은 늦은 처리속도로 인해 실시간 상황인식 서비스에서 빠른 응답을 바라는 사용자의 요구사항을 만족시키기 어렵다. 또한 사례기반추론은 사례기저에 쌓인 사례의 수가 늘어감에 따라 속도가 저하되는 단점이 있다. 이러한 단점을 최소화 하기 위하여 클러스터링 기법이 사용되고 있다. 그러나 클러스터링 기법은 사례기저의 수를 줄여가면서 속도를 유지하기 때문에 기존의 사례가 다시 발생하였을 경우에도 새로운 문제로 인식하게 되는 문제를 가지고 있다. 이러한 문제점을 해결하기 위해서 본 논문에서는 사례기저의 수를 유지하면서 사례기저의 수치화 및 트리구조 관리를 이용하여 기존방법보다 빠른 서비스 컴포지션을 구현하는 방법을 제안한다. 그리고 기존의 서비스 컴포지션 기법과 비교 분석을 통하여 제안하는 기법의 유효함을 확인하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1886-1893
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• 2007

More efforts are required to efficiently operate and manage measured data in AMR(Automatic Meter Reading) and manual meter reading that have not become com:[m yet. As customer complaints increase the most appropriate way of finding solutions is precise and reliable metering of data which should be able to maximize customer satisfactions. In this parer, we designed a data mining technique that recommended the reliability of measured data on manual meter reading and a mCRM(Mobile CRM) system that expanded CRM(Customer Relationship Management). We will propose a mCRM in which the system compares the patterns of customer's using data. W the measured data gathered is outside of a similarity measure(maximum and minimum), it enhances the reliability of measured data by managing this fact in mobile for each customers. We will proposed a system where the mCRM provides customers with reliability and efficiency when related enterprises cannot establish AMR because of the burden of extra costs.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.588-590
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• 2016

사용자의 성별은 기본적이면서도 중요한 마케팅 데이터다. 그러나 최근에는 개인정보보호 강화 추세로, 회원가입 시 성별이나 나이 등의 세부 정보를 입력하지 않는 간편 가입이 많아졌다. 이러한 입력되지 않은 정보 추출을 위해 성별 예측 연구의 필요성이 증가되었다. 성별이 입력된 사용자의 정보를 바탕으로 성별이 입력되지 않은 사용자의 성별을 예측하는 기존 연구가 다양한 방법으로 진행되어왔고, 우수한 식별이 가능한 기법들은 이진분류기인 SVM을 기반으로 한 연구가 다수 존재한다. 그러나 SVM 알고리즘은 이진 분류만 가능하기 때문에 성별예측에 대한 정확률은 알 수가 없다. 성별예측의 정확률을 활용하면 부정확한 분류를 예방할 수 있으며 상품추천의 가중치로 사용 될 수 있다. 본 연구는 확률을 기반으로 하여 정확률을 추론 가능한 나이브 베이지안을 응용한다. 그리고 데이터 집합 사례를 균형있게 늘려주는 SMOTE기법을 이용해 클래스 불균형 문제를 개선했으며 또한 성별 예측의 특성에 맞게 노이즈를 제거하고, 성별 분류에 확정적인 아이템에 가중치를 적용했다. 더불어 제안 방법을 실제 데이터에 적용시켜 우수성을 입증하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.4
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• pp.875-885
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• 2010

CBR (Case-Based Reasoning) is a technique to infer the relationships between existing data and case data, and the method to calculate similarity and Euclidean distance is mostly frequently being used. However, since those methods compare all the existing and case data, it also has a demerit that it takes much time for data search and filtering. Therefore, to solve this problem, various researches have been conducted. This paper suggests the method of SE(Speed Euclidean-distance) calculation that utilizes the patterns discovered in the existing process of computing similarity and Euclidean distance. Because SE calculation applies the patterns and weight found during inputting new cases and enables fast data extraction and short operation time, it can enhance computing speed for temporal or spatial restrictions and eliminate unnecessary computing operation. Through this experiment, it has been found that the proposed method improves performance in various computer environments or processing rate more efficiently than the existing method that extracts data using similarity or Euclidean method does.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.183-190
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• 2009

The core technique of ubiquitous computing is the context aware computing and the context aware technique is more like software so the important research work is to develop the core engines first and the adapted device for the engines. When ubiquitous computing era comes, the current existing internet shopping mall, the form of searching the direct goods and ordering the goods by the customers evolves and develops the form of system that recommends the goods by the search engine which combined with the input data and technique of case based reasoning and intelligent agent that is based on the context aware technique. In this paper, search engine which is based on the case based reasoning and intelligent agent is designed and the prototype is implemented to be adapted to the internet fashion expert shopping mall.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.23-51
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• 2003

With the recent expansion of internet shopping mall, the importance of intelligent products recommendation agents has been increasing. for the products recommendation, This paper propose case-based reasoning approach, and developed a case-based bundle products recommendation system which can recommend a set of sea food used in family events. To apply CBR approach to the bundle products recommendation, it requires the following 4R steps : \circled1 Retrieval, \circled2 Reuse, \circled3 Revise, \circled4 Retain. To retrieve similar cases from the case-base efficiently, case representation scheme is most important. This paper used OW(Object Modeling Technique) to represent bundle products recommendation cases, and developed a similarity measure method to search similar cases. To measure similarity, we used weight-sum approach basically. Especially This paper propose the meaning and uses of taxonomies for representing case features.

• The Journal of Information Technology
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• v.7 no.3
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• pp.127-137
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• 2004

A Project planning is one of the most important processes that determines success and failure of a project. Scope management for a project planning is also essential job in system integration project. However project planning is very difficult because lots of factors and their relationships should be considered. Therefore project planning of system integration project has been done by project manager's own knowledge and experience. It is necessary to develop an algorithm of WBS(Work Breakdown Structure) identification & document selection along to project's specificity in project management system using AI technique. This study presents a methodology to cope with the limitations of the existing studies that have uniformly been customizing the methodology by only project complexity. We propose PPSM(Project planning support module) based on determination rules regarding route maps and document levels, and CBR(Case-Based Reasoning) for WBS identification.

• Korean Journal of Construction Engineering and Management
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• v.7 no.2 s.30
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• pp.138-147
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• 2006

The objective of this research is to explore a more precise forecasting method by applying Case-based Reasoning (CBR). The newly suggested method in this study enables project managers to forecast monthly expenditures with less time and effort by retrieving and referring only projects of a similar nature, while filtering out irrelevant cases included in database. For the purpose of accurate forecasting, 1) the choice of the numbers of referring projects and 2) the better selection among three levels ? which include a 20-work package level, a 7-major work package level, and a total sum level analysis, were investigated in detail. It is concluded that selecting similar projects at $12{\sim}19%$ out of the whole database will produce a more precise forecasting. The new forecasting model, which suggests the predicted values based on previous projects, is more than just a forecasting methodology; it provides a bridge that enables current data collection techniques to be used within the context of the accumulated information. This will eventually help all the participants in the construction industry to build up the knowledge derived from invaluable experience.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.175-182
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• 2008

Context-aware service environment should provide many kinds of services according to users' requests. Users want a great variety of services. In response to their demands the service provider should make a new service every time. But making a new service every time may be inefficient even for a small number of users' requests. So, there are studies on how to efficiently support various and complex requests fFom users. In many researches, service compositions have lately attracted considerable attention. However, existing researches have mainly focused on Web services. So they are not proper to rapidly providing services in response to users' requests, especially In context-aware service environment. This paper proposes a rapid service composition using case-based reasoning. For evaluating the proposed algorithm we implement 'purchasing seTvice agent'. With this system, we compare our algorithm and the existing service composition algorithms.

• Journal of Korean Society of societal Security
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• v.4 no.2
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• pp.29-40
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• 2011

The objective of this paper is to develop an intelligent decision support system that is able to advise disaster countermeasures and degree of incidents on the basis of the collected and analyzed signs of disasters. The concepts derived from ontology, text mining and case-based reasoning are adapted to design the system. The functions of this system include term-document matrix, frequency normalization, confidency, association rules, and criteria for judgment. The collected qualitative data from signs of new incidents are processed by those functions and are finally compared and reasoned to past similar disaster cases. The system provides the varying degrees of how dangerous the new signs of disasters are and the few countermeasures to the disaster for the manager of disaster management. The system will be helpful for the decision-maker to make a judgment about how much dangerous the signs of disaster are and to carry out specific kinds of countermeasures on the disaster in advance. As a result, the disaster will be prevented.