• 한국수학사학회지
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• 제18권2호
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• pp.95-106
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• 2005

본 논문에서는 수학을 기반으로 한 데이터베이스의 지식탐사 절차를 통하여 데이터의 선택, 정제, 통합, 변환, 축소, 데이터 마이닝 기법의 선택과 적용 및 모형의 평가에 관한 개념과 방법론을 소개하고 수학의 한 분야로서 통계학의 역할과 적용방법에 관하여 연구하고자 한다. 또한 오늘날 관심이 대상이 되고 있는 데이터 마이닝의 역사와 수학적 배경, 통계 및 정보 기술을 이용한 데이터 마이닝의 주요 모델링 기법, 실용적 응용 분야 및 적용 사례 그리고 데이터 마이닝과 통계의 차이점에 관하여 조사하고 논하고자 한다.

• 산업경영시스템학회지
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• 제21권45호
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• pp.101-112
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• 1998

Data mining, which is also referred to as knowledge discovery in database, means a process of nontrivial extraction of implicit, previously unknown and potentially useful information (such as knowledge rules, constraints, regularities) from data in databases. The discovered knowledge can be applied to information management, decision making, and many other applications. In this paper, a new data mining problem, discovering sequential patterns, is proposed which is to find all sequential patterns using sampling method. Recognizing that the quantity of database is growing exponentially and transaction database is frequently updated, sampling method is a fast algorithm reducing time and cost while extracting the trend of customer behavior. This method analyzes the fraction of database but can in general lead to results of a very high degree of accuracy. The relaxation factor, as well as the sample size, can be properly adjusted so as to improve the result accuracy while minimizing the corresponding execution time. The superiority of the proposed algorithm will be shown through analyzing accuracy and efficiency by comparing with Apriori All algorithm.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 가을 학술발표논문집 Vol.31 No.2 (2)
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• pp.187-189
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• 2004

최근 정보기술의 가속적인 발전과 인터넷의 급속한 보급으로 인하여 우리는 다양하고 방대한 양의 지역정보를 접하고 이용하고 있다. 그러나 지역개발사업을 추진하는데 있어서 계획수립이 차지하는 중요성이 매우 큼에도 불구하고 지역을 대표하는 객관적이고 유용한 정보를 찾아내어 지역개발계획수립에 활용하는 예는 거의 없었다. 이에 여러 곳에 산재되어있는 지역정보들을 통합하여 관리하고 이러한 대량의 지역 데이터들로부터 지역을 특징지을 수 있는 보다 현실적이고 유용한 정보를 추출하거나 생성하여 지역정보 분석에 활용하는 방법이 필요하게 되었다. 본 논문에서는 지역개발계획을 수립하는데 있어서 방대한 양의 데이터로부터 유용한 정보를 추출하고 발견하는 지식발견(KDD : Knowledge Discovery in Database)(1) 프로세서의 전체과정에 지역개발계획 수립 목적에 맞추어 지역개발이론에 기초한 지역정보 분석과정을 삽입함으로써 보다 합리적이고 현실적인 지역개발계획이 수립되도록 지원할 수 있는 프로세서를 설계한다.

• 한국농공학회지
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• 제45권6호
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• pp.183-193
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• 2003

Most construction works on the soft ground adopt instrumentation to manage settlement and stability of the embankment. The rapid progress of the information technologies and the digital data acquisition on the soft ground instrumentation has led to the fast-growing amount of data. Although valuable information about the behaviour of the soft ground may be hiding behind the data, most of the data are used restrictedly only for the management of settlement and stability. One of the critical issues on soft ground instrumentation is the long-term settlement prediction. Some observational settlement analysis methods are used for this purpose. But the reliability of the analysis results is remained in vague. The knowledge could be discovered from a large volume of experiences on the observational settlement analysis. In this article, we present a database to store settlement records and data mining procedure. A large volume of knowledge about observational settlement prediction were collected from the database by applying the filtering algorithm and knowledge discovery algorithm. Statistical analysis revealed that the reliability of observational settlement analysis depends on stay duration and estimated degree of consolidation.

• 산업공학
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• 제14권2호
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• pp.164-171
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• 2001

We suggest a Business Performance Information System with Knowledge Discovery in Databases(KDD) as a key component of integrated information and knowledge management system. The proposed system measures business performance by considering both VA(Value-Added), which represents stakeholder's point of view and EVA(Economic Value-Added), which represents shareholder's point of view. In modeling of Business Performance Information System, we apply the following KDD processes : Data Warehouse for consistent management of a performance data, On-Line Analytic Processing(OLAP) for multidimensional analysis, Genetic Algorithms for exploring and finding dominant managing factors and Analytic Hierarchy Process(AHP) for applying expert's knowledge and experience. To demonstrate the performance of the system, we conducted a case study using financial data of Korean automobile industry over 16 years from 1981 to 1996, which is taken from database of KISFAS(Korea Investors Services Financial Analysis System).

• 정보처리학회논문지B
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• 제9B권5호
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• pp.635-642
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• 2002

정보 기술 분야의 지능화 요구는 매우 빠르게 증가하고 있다. 특히 대량의 데이터로부터 지식을 찾아내어 최적의 의사결정을 해야하는 KDD(Knowledge Discovery in Database)분야에서는 그 요구가 더욱 더 크게 된다. 지능화된 의사결정을 위해서는 대용량 지식 베이스(Knowledge Base)의 효율적인 관리가 무엇보다도 중요하다. 본 논문에서는 이러한 지식 베이스로부터 의사결정 관리에 필요한 지식을 얻기 위해 효율적으로 지식 베이스를 검색하고 갱신하는 관리 방법을 위해 자율학습 신경망인 자기조직화 지도에 확률적 분포 이론을 결합한 하이브리드(Hybrid) SOM을 제안한다. 제안 방법을 이용한 효율적 지식 베이스의 관리를 시뮬레이션 실험을 통하여 수행하였다. 실험을 통해 본 논문에서 제안하는 Hybrid SOM이 지식 베이스 관리에 효율적인 성능을 나타냄이 증명되었다.

• 한국경영과학회지
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• 제25권3호
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• pp.91-107
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• 2000

The linear programming model is a special form of useful knowledge that is embedded in a database. Since formulating models from scratch requires knowledge-intensive efforts, knowledge-based formulation support systems have been proposed in the Decision Support Systems area. However, they rely on the assumption that sufficient domain knowledge should already be captured as a specific knowledge representation form. Hence, the purpose of this paper is to propose a methodology that finds useful knowledge on building linear programming models from a database. The methodology consists of two parts. The first part is to find s first-cut model based on a data dictionary. To do so, we applied the General Problem Solver(GPS) algorithm. The second part is to discover a second-cut model by applying neural network technique. An illustrative example is described to show the feasibility of the proposed methodology.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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• pp.125-133
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• 1999

The objective of knowledge discovery and data mining lies in the generation of useful insights from a store of data. This paper presents a framework for knowledge mining to provide a systematic approach to the selection and deployment of tools for automated learning. Every methodology has its strengths and limitations. Consequently, a multistrategy approach may be required to take advantage of the strengths of disparate technique while circumventing their individual limitations. For concreteness, the general framework for data mining in marketing is examined in the context of developing agents for optimizing a supply chain network.

• 한국정보시스템학회지:정보시스템연구
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• 제2권
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• pp.194-206
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• 1993

Intelligent remote learning system is a system that incorporate communication technology and others : a database engine, an intelligent tutorial system. Learners can study by themselves through the intelligent tutorial system. The existence of a communication, database and artificial intelligence enhance the capability of IRLS. According to Parsaye, an intelligent databases should have the following features : 1) Knowledge discovery. 2) Data integrity and quality control. 3) Hypermedia management. 4) Data presentation and display. 5) Decision support and scenario analysis. 6) Data format management. 7) Intelligent system design tools. I hope that this research of framework for IRLS paves for the future research. As mentioned in the above, the future work will include an intelligent database, self-learning mechanism using neural network.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1998년도 국제 컨퍼런스: 국가경쟁력 향상을 위한 디지틀도서관 구축방안
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• pp.83-98
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• 1998

Who needs Media Asset Management？ ◆ Publishers ◆ Any company publishing newspapers, magazines, catalogs or web sites. ◆ Content Creators ◆ Companies who create content for use in their business ◆ Broadcasters, Advertising Agencies, Studios, Sports Houses (NBA, NFL), Corporate Training Depts, Retailers ◆ Content Distributors ◆ Cable Operators, Telecoms, Internet Service Providers, Online Service Providers Who needs Media Asset Management？ ◆ There's a LOT of money being spent on this kind of technology, and not just by 'media' companies ◆ Retailers, for catalogs, web sites, call centers ◆ Chems/Pharms, for drug. discovery, knowledge management ◆ Legal, for document and knowledge management ◆ Federal, for video surveillance and knowledge management ◆ Manufacturing, for integration of CAD, text and business-to-business applications ◆ Anyone with a Web/Content Management challenge(omitted)