• Title/Summary/Keyword: Knowledge-based rules

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Knowledge-Based AOP Framework for Business Rule Aspects in Business Process

  • Park, Chan-Kyu;Choi, Ho-Jin;Lee, Dan-Hyung;Kang, Sung-Won;Cho, Hyun-Kyu;Sohn, Joo-Chan
    • ETRI Journal
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    • v.29 no.4
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    • pp.477-488
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    • 2007
  • In recent years, numerous studies have identified and explored issues related to web-service-oriented business process specifications, such as business process execution language (BPEL). In particular, business rules are an important cross-cutting concern that should be distinguished from business process instances. In this paper, we present a rule-based aspect oriented programming (AOP) framework where business rule aspects contained in business processes can be effectively separated and executed. This is achieved by using a mechanism of the business rule itself at the business rule engine instead of using existing programming language-based AOP technologies. Through some illustrative examples, this work also introduces a method by which business rule aspects, separated through an external rule engine, can be represented and evaluated. We also demonstrate how they can be dynamically woven and executed by providing an implementation example which uses two open-source-based products, the Mandarax rules engine and Bexee BPEL engine.

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A Study on the Construction of the Automatic Summaries - on the basis of Straight News in the Web - (자동요약시스템 구축에 대한 연구 - 웹 상의 보도기사를 중심으로 -)

  • Lee, Tae-Young
    • Journal of the Korean Society for information Management
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    • v.23 no.4 s.62
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    • pp.41-67
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    • 2006
  • The writings frame and various rules based on discourse structure and knowledge-based methods were applied to construct the automatic Ext/sums (extracts & summaries) system from the straight news in web. The frame contains the slot and facet represented by the role of paragraphs, sentences , and clauses in news and the rules determining the type of slot. Rearrangement like Unification, separation, and synthesis of the candidate sentences to summary, maintaining the coherence of meanings, was carried out by using the rules derived from similar degree measurement, syntactic information, discourse structure, and knowledge-based methods and the context plots defined with the syntactic/semantic signature of noun and verb and category of verb suffix. The critic sentence were tried to insert into summary.

eXtensible Rule Markup Language (XRML): Design Principles and Application (확장형 규칙 표식 언어(eXtensible Rule Markup Language) : 설계 원리 및 응용)

  • 이재규;손미애;강주영
    • Journal of Intelligence and Information Systems
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    • v.8 no.1
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    • pp.141-157
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    • 2002
  • extensible Markup Language (XML) is a new markup language for data exchange on the Internet. In this paper, we propose a language extensible Rule Markup Language (XRML) which is an extension of XML. The implicit rules embedded in the Web pages should be identifiable, interchangeable with structured rule format, and finally accessible by various applications. It is possible to realize by using XRML. In this light, Web based Knowledge Management Systems (KMS) can be integrated with rule-based expert systems. To meet this end, we propose the six design criteria: Expressional Completeness, Relevance Linkability, Polymorphous Consistency, Applicative Universality, Knowledge Integrability and Interoperability. Furthermore, we propose three components such as RIML (Rule Identification Markup Language), RSML (Rule Structure Markup Language) and RTML (Rule Triggering Markup Language), and the Document Type Definition DTD). We have designed the XRML version 0.5 as illustrated above, and developed its prototype named Form/XRML which is an automated form processing for disbursement of the research fund in the Korea Advanced Institute of Science and Technology (KAISI). Since XRML allows both human and software agent to use the rules, there is huge application potential. We expect that XRML can contribute to the progress of Semantic Web platforms making knowledge management and e-commerce more intelligent. Since there are many emerging research groups and vendors who investigate this issue, it will not take long to see XRML commercial products. Matured XRML applications may change the way of designing information and knowledge systems in the near future.

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A Model with an Inference Engine for a Fuzzy Production System Using Fuzzy Petri Nets (Fuzzy Petri Nets를 이용한 퍼지 추론 시스템의 모델링 및 추론기관의 구현)

  • ;Zeung Nam Bien
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.7
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    • pp.30-41
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    • 1992
  • As a general model of rule-based systems, we propose a model for a fuzzy production system having chaining rules and an inference engine associated with the model. The concept of so-called 'fuzzy petri nets' is used to model the fuzzy production system and the inference engine is designed to be capable of handling inexact knowledge. The fuzzy logic is adopted to represent vagueness in the rules and the certainty factor is used to express uncertainty of each rules given by a human expert. Parallel, inference schemes are devised by transforming Fuzzy Petri nets to matrix formula. Futher, the inference engine mechanism under the Mamdani's implication method can be desceribed by a simple algebraic formula, which makes real time inference possible.

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A Knowledge Based Physical Activity Evaluation Model Using Associative Classification Mining Approach (연관 분류 마이닝 기법을 활용한 지식기반 신체활동 평가 모델)

  • Son, Chang-Sik;Choi, Rock-Hyun;Kang, Won-Seok
    • IEMEK Journal of Embedded Systems and Applications
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    • v.13 no.4
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    • pp.215-223
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    • 2018
  • Recently, as interest of wearable devices has increased, commercially available smart wristbands and applications have been used as a tool for personal healthy management. However most previous studies have focused on evaluating the accuracy and reliability of the technical problems of wearable devices, especially step counts, walking distance, and energy consumption measured from the smart wristbands. In this study, we propose a physical activity evaluation model using classification rules, induced from the associative classification mining approach. These rules associated with five physical activities were generated by considering activities and walking times in target heart rate zones such as 'Out-of Zone', 'Fat Burn Zone', 'Cardio Zone', and 'Peak Zone'. In the experiment, we evaluated the prediction power of classification rules and verified its effectiveness by comparing classification accuracies between the proposed model and support vector machine.

HYBRID PID FLC using sliding Mode (슬라이딩 모드를 이용한 HYBRID PID형 퍼지제어기)

  • Moon, Jun-Ho;Cho, Jong-Hoon;Oh, Kwang-Hyun;Kim, Tae-Un;Nam, Moon-Hyen
    • Proceedings of the KIEE Conference
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    • 1995.07b
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    • pp.992-994
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    • 1995
  • FLC has a good performance for complication system or unknown model by using human linguistic method but many part control design are based on expert knowledge or trial-error method and it is difficult to prove stability and robustness of controller. In this paper we improve this problem by setting fuzzy rules by dividing phase plane of error and rate of error change by switching surface. We can guarantee the stability in nonlinear system, and also in fuzzy PID type controller the complexity of controller design is increased by increasing the number of input variables and defining more range of operation if we want performance of more specific rules, thus we need to fine the method to decrease the number of control rules used in FLC design. In this paper the algorithm is validated by simulation using conventional FLC and proposed method.

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Design of the Fuzzy Controller with Adaptive Membership Function to Inverted Pendulum Swing-up Control (도립진자의 스윙-엎 제어를 위한 적응형 소속함수를 갖는 퍼지제어기 설계)

  • Shin, Ja-Ho;Hong, Dae-Seung;Ryu, Chang-Wan;Yim, Wha-Yeong
    • Proceedings of the KIEE Conference
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    • 2000.07d
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    • pp.2492-2494
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    • 2000
  • Design of Fuzzy cotroller consists of intuition of human expert, and any other information about how to control system. If the rules adequately control the system, the design work is done well. If the rules are inadequate, the designer must modify the rules. Through this procedure, the system can be controlled. In this paper, we designed simply a fuzzy controller based on human knowledge, but it has errors showing some vibrations. So we updated the optimal parameters of fuzzy controller using Neural Network algorithm.

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Integrating Case-Based Reasoning with DSS (DSS와 사례기반 추론의 결합)

  • Kim Jin-Baek
    • Management & Information Systems Review
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    • v.2
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    • pp.169-193
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    • 1998
  • Case- based reasoning(CBR) offers a new approach for developing knowledge based systems. Unlike the rule-based paradigm, in which domain knowledge is encoded in the form of production rules, in the case-based approach the problem solving experience of the domain expert is encoded in the form of cases stored in a casebase(CB). CBR allows a reasoner (1) to propose solutions in domains that are not completely understood by the reasoner, (2) to evaluate solutions when no algorithmic method is available for evaluation, and (3) to interprete open-ended and ill-defined concepts. CBR also helps reasoner (4) take actions to avoid repeating past mistakes, and (5) focus its reasoning on important parts of a problem. Owing to the above advantages, CBR has successfully been applied to many kinds of problems such as design, planning, diagnosis and instruction. In this paper, I propose case-based DSS(CBDSS). CBDSS is an intelligent DSS using CBR technique. CBDSS consists of interface, case-based reasoner, maintainer, casebase management system, domain dependent CB, domain independent CB, and so on.

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Intention Classification for Retrieval of Health Questions

  • Liu, Rey-Long
    • International Journal of Knowledge Content Development & Technology
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    • v.7 no.1
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    • pp.101-120
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    • 2017
  • Healthcare professionals have edited many health questions (HQs) and their answers for healthcare consumers on the Internet. The HQs provide both readable and reliable health information, and hence retrieval of those HQs that are relevant to a given question is essential for health education and promotion through the Internet. However, retrieval of relevant HQs needs to be based on the recognition of the intention of each HQ, which is difficult to be done by predefining syntactic and semantic rules. We thus model the intention recognition problem as a text classification problem, and develop two techniques to improve a learning-based text classifier for the problem. The two techniques improve the classifier by location-based and area-based feature weightings, respectively. Experimental results show that, the two techniques can work together to significantly improve a Support Vector Machine classifier in both the recognition of HQ intentions and the retrieval of relevant HQs.