• International Journal of Contents
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• v.5 no.3
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• pp.79-85
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• 2009

Emergent requests or urgent information among enterprises require their intimate collaboration in B2B EC (electronic commerce). This paper analyzes the needs of intimate cooperation of distributed EC systems in terms of business contracts and presents an active rule-based methodology of close cooperation among EC systems and an active rule component to support it. Since the rule component provides high level rule patterns and event-based immediate processing, system administrators and programmers can easily program and maintain intimate cooperation of distributed EC systems independently to the application logic. The proposed active rule component facilitates HTTP protocol. Its prototype is implemented in B2B EC environment and evaluated using basic trigger facility of a commercial DBMS.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.353-359
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• 2005

In this research, we propose a Unified Fuzzy rule-based knowledge Inference Systems (UFIS) to help the expert in cosmetic brand detection. Users' preferred cosmetic product detection is very important in the level of CRM. To this purpose, many corporations trying to develop an efficient data mining tool. In this study, we develop a prototype fuzzy rule detection and inference system. The framework used in this development is mainly based on two different mechanisms such as fuzzy rule extraction and RDB (Relational DB)-based fuzzy rule inference. First, fuzzy clustering and fuzzy rule extraction deal with the presence of the knowledge in data base and its value is presented with a value between 0 -1. Second, RDB and SQL (Structured Query Language)-based fuzzy rule inference mechanism provide more flexibility in knowledge management than conventional non-fuzzy value-based KMS (Knowledge Management Systems).

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.81-89
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• 2014

In Korea, National spatial data infrastructure has implemented in order to integrated manage and share the national spatial information producted by public agencies and local governments. The necessities of systematic quality management are raised, because information, which is generated by different agencies, is integrative managed by national level. In this paper, the establishment of BPR(Business Process Reengineering) for national spatial data infrastructure quality management system. Quality management business is defined as quality management object definition, quality measuring, evaluation and analysis, and quality enhancement process. Next, activities for each process are designed. For the quality management business, business rule(BR) is required for determining error. We derive the BR for six objects(legal-dong, railway boundary, railway centerline, road boundary, road centerline, building) among the basic spatial information. Other information's BR can be generated by using the derivation method described in this paper. Based on the BPR of this paper and derived BR, national spatial data infrastructure quality management system can be implemented in the future.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.369-374
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• 2004

기업 내부에 존재하는 비즈니스 룰은 정형화되고 집중화된 하나의 시스템으로 구축되어 있는 것이 아니라 여러 서브시스템이나 실무자들의 경험 속에 산재되어 존재한다. 산재되어 존재하는 비즈니스 룰을 정형화된 형태로 집중관리가 가능하도록 구축한 도구가 BRE(Business Rule Engine)이다. BRE는 비즈니스 룰 관리를 빠르고 용이하게 하여, 기업의 경쟁력 향상에 매우 효과적인 기여를 한다. 본 연구에서는 BRE도입의 적합성 여부를 평가할 수 있는 모델을 제시한다. 본 연구의 결과를 활용하면 기업은 용이하게 BRE도입 여부를 판단할 수 있어 기업의 경쟁력을 향상시킬 수 있을 것이다.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.764-770
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• 2004

This paper presents a hybrid data mining mechanism to extract expert knowledge from historical data and extend expert systems' reasoning capabilities by using fuzzy neural network (FNN)-based learning & rule extraction algorithm. Our hybrid data mining mechanism is based on association rule extraction mechanism, FNN learning and fuzzy rule extraction algorithm. Most of traditional data mining mechanisms are depended ()n association rule extraction algorithm. However, the basic association rule-based data mining systems has not the learning ability. Therefore, there is a problem to extend the knowledge base adaptively. In addition, sequential patterns of association rules can`t represent the complicate fuzzy logic in real-world. To resolve these problems, we suggest the hybrid data mining mechanism based on association rule-based data mining, FNN learning and fuzzy rule extraction algorithm. Our hybrid data mining mechanism is consisted of four phases. First, we use general association rule mining mechanism to develop an initial rule base. Then, in the second phase, we adopt the FNN learning algorithm to extract the hidden relationships or patterns embedded in the historical data. Third, after the learning of FNN, the fuzzy rule extraction algorithm will be used to extract the implicit knowledge from the FNN. Fourth, we will combine the association rules (initial rule base) and fuzzy rules. Implementation results show that the hybrid data mining mechanism can reflect both association rule-based knowledge extraction and FNN-based knowledge extension.

• Proceedings of the CALSEC Conference
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• 2004.02a
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• pp.318-326
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• 2004

The ebXML (Electronic Business using eXtensible Markup Language) Specification Schema is to provide nominal set of specification elements necessary to specify a collaboration between business partners based on XML. As a part of ebXML Specification Schema, BPSS (Business Process Specification Schema) has been provided to support the direct specification of the set of elements required to configure a runtime system in order to execute a set of ebXML business transactions. The BPSS is available in two stand-alone representations, a UML version and an XML version. Due to the limitations of UML notations and XML syntax, however, current ebXML BPSS specification is insufficient to specify formal semantic constraints of modeling elements completely. In this study, we propose a classification schema for the BPSS semantic constraints and describe how to represent those semantic constraints formally using OCL (Object Constraint Language). As a way to verify a Business Process Specification (BPS) with the formal semantic constraint modeling, we suggest a rule-based approach to represent the formal constraints and to use the rule-based constraints specification to verify BPSs in a CLIPS prototype implementation.

• Information Systems Review
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• v.8 no.2
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• pp.119-138
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• 2006

Association Rule Mining has been successfully used for mining knowledge in static environment but it provides limited features to discovery time-dependent knowledge from multi-point data set. The aim of this paper is to develop a methodology which detects changes of customer behavior automatically from customer profiles and sales data at different multi-point snapshots. This paper proposes a procedure named 'Recursive Change Mining' for detecting continuous change of customer purchase behavior. The Recursive Change Mining Procedure is basically extended association rule mining and it assures to discover continuous and repetitive changes from data sets which collected at multi-periods. A case study on L department store is also provided.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.619-622
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• 2005

최근 금융권의 수익 기반이 되고 있는 수수료는 다양한 형태의 규칙을 내포하고 있으며, 복잡성이 증가하고 있어 유연하고 동적인 수수료 구조가 요구된다. 이러한 요구 사항을 충족시키기 위해서 업무 규칙(business rule)이 활용될 수 있다. 본 논문에서는 은행권의 수수료를 분석하여, 수수료 부과 기준을 업무 규칙으로 정의하고, 이를 파라미터 드리븐(parameter driven) 방식의 룰 데이터베이스(rule database)로 설계하였다. 이를 통하여 복합 수수료를 즉시 적용할 수 있는 유연한 설계로 어플리케이션 구조를 단순화 할 수 있는 업무 규칙 기반 수수료 처리 컴포넌트를 설계하였다.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.2
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• pp.129-140
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• 2006

The existing CBD development methods deal with the analysis phase in a superficial manner. Applying such a superficial analysis to business applications with a number of subsystems makes analysis models be inconsistent with levels and styles, only depending on experiences of the analysts. This inconsistent analysis might cause more serious problems during the subsequent development phases, resulting in the failure of the projects. In this paper, we propose a rule-based analysis pattern that provides an analysis template for business applications. This pattern analyzes the concepts of business applications by using external events and internal rules that process the events. Employing this pattern, a huge business application can be developed by a couple of co-analysts who work together in a consistent and systematic manner. This paper also describes an efficient way to develop business components with the suggested analysis pattern using banking deposit case study through UML Components development process.

• The Journal of Information Systems
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• v.18 no.4
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• pp.59-86
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• 2009

Data modeling can be regarded as a series of processes to abstract real-world business concerns. The conceptual modeling phase is often regarded as the most difficult stage in the entire modeling process, because quite different conceptual models may be produced even for similar business domains based on users' varying requirements and the data modelers' diverse perceptions of the requirements. This implies that an object considered as an entity in one domain may be considered as an attribute in another, and vice versa. However, many traditional knowledge-based automated database design systems unfortunately fail to construct appropriate Entity-Relationship Diagrams(ERDs) for a given set of requirements due to the rigid assumption that an object should be classified as an entity if it has been classified as an entity in previous applications. In this paper, we propose an alternative automation system which can generate ERDs from business descriptions using association rule mining technique. Our system can be differentiated from the traditional ones in that our system can perform data modeling only based on business description written by domain workers, rather than relying on any kind of knowledge base. Since the proposed system can produce various versions of ERDs from the same business descriptions simultaneously, users can have the opportunity to choose one of the ERDs as being the most appropriate, based on their business environment and requirements. We performed a case study for personnel management in a university to evaluate the practicability of the proposed system This paper summarizes the result of it in the experiment section.