• Title/Summary/Keyword: knowledge-based approach

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An intelligent system for automatic data extraction in E-Commerce Applications

  • Cardenosa, Jesus;Iraola, Luis;Tovar, Edmundo
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2001.01a
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    • pp.202-208
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    • 2001
  • One of the most frequent uses of Internet is data gathering. Data can be about many themes but perhaps one of the most demanded fields is the tourist information. Normally, databases that support these systems are maintained manually. However, there is other approach, that is, to extract data automatically, for instance, from textual public information existing in the Web. This approach consists of extracting data from textual sources(public or not) and to serve them totally or partially to the user in the form that he/she wants. The obtained data can maintain automatically databases that support different systems as WAP mobile telephones, or commercial systems accessed by Natural Language Interfaces and others. This process has three main actors. The first is the information itself that is present in a particular context. The second is the information supplier (extracting data from the existing information) and the third is the user or information searcher. This added value chain reuse and give value to existing data even in the case that these data were not tough for the last use by the use of the described technology. The main advantage of this approach is that it makes independent the information source from the information user. This means that the original information belongs to a particular context, not necessarily the context of the user. This paper will describe the application based on this approach developed by the authors in the FLEX EXPRIT IV n$^{\circ}$EP29158 in the Work-package "Knowledge Extraction & Data mining"where the information captured from digital newspapers is extracted and reused in tourist information context.

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Borderlines in Early Childhood Teacher's Practical Knowledge of 'Curriculum' via Metaphor Analysis (메타포를 통해 본 유아교사의 '교육과정'에 대한 실천적 지식의 한계)

  • Lee, Kyeong Hwa
    • Korean Journal of Childcare and Education
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    • v.12 no.4
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    • pp.131-149
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    • 2016
  • Teacher's practical knowledge is potentially relevant to the teaching practice in his/her classroom. The research explored early childhood teachers' practical knowledge of 'curriculum' via conceptual metaphors. The participants (N=348) completed a prompt, "Curriculum is like A because B" and then the metaphors were analyzed according to the procedure proposed by Moser (2000). The analysis found that 8 themes (i.e. 'educational basis', 'learning opportunity', 'educational material', 'difficulty', 'change', 'pre-determination', 'discordance', and 'reconstruction') were the underlying conceptions signified in those metaphors. The implications regarding early childhood teachers' practical knowledge were discussed on the perspective of post-modern curriculum. Moreover, it recommended the practical knowledge based approach for early childhood teacher education, and transformation of current policy for program evaluation relevant to curriculum conceptualization.

An Index-Based Context-Aware Energy Management System in Ubiquitous Smart Space (유비쿼터스 지능 공간에서의 지수 기반 상황인지 에너지경영 시스템)

  • Kwon, Ohyung;Lee, Yonnim
    • Knowledge Management Research
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    • v.9 no.4
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    • pp.51-63
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    • 2008
  • Effective energy consumption now becomes one of the area of knowledge management which potentially gives global impact. It is considerable for the energy management to optimize the usage of energy, rather than decreasing energy consumption at any cases. To resolve these challenges, an intelligent and personalized system which helps the individuals control their own behaviors in an optimal and timely manner is needed. So far, however, since the legacy energy management systems are nation-wide or organizational, individual-level energy management is nearly impossible. Moreover, most estimating methods of energy consumption are based on forecasting techniques which tend to risky or analysis models which may not be provided in a timely manner. Hence, the purpose of this paper is to propose a novel individual-level energy management system which aims to realize timely and personalized energy management based on context-aware computing approach. To do so, an index model for energy consumption is proposed with a corresponding service framework.

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A Development of Blind Force Control of Robot for Grind Automation (사상 자동화를 위한 로봇의 Blind Force Control 기술 개발)

  • Lee Woo-Won;Park Chan-Ho;Lim Kye-Young
    • Proceedings of the KIPE Conference
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    • 2006.06a
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    • pp.158-162
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    • 2006
  • A lot of pieces of iron plate are used to build a ship. The states of cutting surface of iron are however bended or ununiformly cuttled by cutting machine. These may cause bad Quality of painting, and shorter lifetime of iron by rust. In this paper, a new approach of grinding force control method which teaching of robot is not required is proposed to avoid long preparation time of robot and to improve the productivity. The way used in this paper is just like a blind man works through the road with stick only.

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Design of Fuzzy Controller Based on Empirical Knowledge (실험적 지식에 기초한 퍼지제어기 설계)

  • Bae, Hyeon;Kim, Sung-Shin;Kim, Hae-Gyun
    • Proceedings of the KIEE Conference
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    • 2000.07d
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    • pp.2296-2298
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    • 2000
  • Fuzzy control has been researched for application of industrial processes which have no accurate mathematical model and could not controlled by conventional methods because of a lack of quantitative input-output data. Intelligent control approach based on fuzzy logic could directly reflex human thinking and natural language to controller comparing with conventional methods. In this paper, fuzzy controller is implemented to acquire operator's knowledge. The tested system is constructed for sending a ball to the goal position using wind from two DC motors in the path. This system contains non-linearity and uncertainty because of the characteristic of aerodynamics inside the path. Ball position is measured by a vision camera. The system used in this experiment could be hardly modeled by mathematic methods and could not be easily controlled by linear control manners. The controller, in this paper is designed based on the input-output data and experimental knowledge obtained by trials.

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A Study on Fault Diagnostic Model for Behaviour Appearance of Components (부품의 가동형태에 따른 고장진단 모델 연구)

  • 박주식;하정호;강경식
    • Journal of the Korea Safety Management & Science
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    • v.4 no.4
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    • pp.97-108
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    • 2002
  • This study deals with the application of knowledge-based engineering and a methodology for the assessment & measurement of reliability, availability, maintainability, and safety of industrial systems using fault-tree representation. A fuzzy methodology for fault-tree evaluation seems to be an alternative solution to overcome the drawbacks of the conventional approach. To improve the quality of results, the membership functions must be approximated based on heuristic considerations. Conventionally, it is not always easy to obtain a system reliability for components with different individual failure probability density functions(p.d.f.), We utilize fuzzy set theory to solve the adequacy of the conventional probability in accounting and processing of built-in uncertainties in the probabilistic data. The purpose of this study is to propose the framework of knowledge-based engineering through integrating the various sources of knowledge involved in a FTA.

Development of a knowledge-based medical expert system to infer supportive treatment suggestions for pediatric patients

  • Ertugrul, Duygu Celik;Ulusoy, Ali Hakan
    • ETRI Journal
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    • v.41 no.4
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    • pp.515-527
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    • 2019
  • This paper discusses the design, implementation, and potential use of an ontology-based mobile pediatric consultation and monitoring system, which is a smart healthcare expert system for pediatric patients. The proposed system provides remote consultation and monitoring of pediatric patients during their illness at places distant from medical service areas. The system not only shares instant medical data with a pediatrician but also examines the data as a smart medical assistant to detect any emergency situation. In addition, it uses an inference engine to infer instant suggestions for performing certain initial medical treatment steps when necessary. The applied methodologies and main technical contributions have three aspects: (a) pediatric consultation and monitoring ontology, (b) semantic Web rule knowledge base, and (c) inference engine. Two case studies with real pediatric patients are provided and discussed. The reported results of the applied case studies are promising, and they demonstrate the applicability, effectiveness, and efficiency of the proposed approach.

Learning from Instruction: A Comprehension-Based Approach (지시문을 통한 학습: 이해-기반 접근)

  • Kim, Shin-Woo;Kim, Min-Young;Lee, Jisun;Sohn, Young-Woo
    • Korean Journal of Cognitive Science
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    • v.14 no.3
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    • pp.23-36
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    • 2003
  • A comprehension-based approach to learning assumes that incoming information and background knowledge are integrated to form a mental representation which is subsequently used to incorporate new knowledge. It is demonstrated that this approach can be validated by comparing human and computational model performance in the prompt learning context. A computational model (ADAPT-UNIX) based on the construction-integration theory of comprehension (Kintsch, 1988; 1998) predicted how users learn from help prompts which are designed to assist UNIX composite command production. In addition, the comparison also revealed high similarity in composite production task performance between model and human. Educational implications of present research are discussed on the basis of the fact that prompt instructions have differential effect on learning and application as background knowledge varies.

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An Extended AND-OR Graph-based Simulation and Electronic Commerce

  • Lee, Kun-Chang;Cho, Hyung-Rae
    • Proceedings of the Korea Society for Simulation Conference
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    • 1999.04a
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    • pp.242-250
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    • 1999
  • The objective of this paper is to propose an Extended AND-OR Graph (EAOG)-driven inferential simulation mechanism with which decision makers engaged in electronic commerce (EC) can effectively deal with complicated decision making problem. In the field of traditional expect systems research, AND-OR Graph approach cannot be effectively used in the EC problems in which real-time problem-solving property should be highly required. In this sense, we propose the EAOG inference mechanism for EC problem-solving in which heurisric knowledge necessary for intelligent EC problem-solving can be represented in a form of matrix. The EAOG method possesses the following three characteristics. 1. Realtime inference: The EAOG inference mechanism is suitable for the real-time inference because its computational mechanism is based on matrix computation.2. Matrix operation: All the subjective knowledge is delineated in a matrix form, so that inference process can proceed based on the matrix operation which is computationally efficient.3. Bi-directional inference: Traditional inference method of expert systems is based on either forward chaining or based on either and computational efficiency. However, the proposed EAOG inference mechanism is generically bi-directional without loss of both speed and efficiency.We have proved the validity of our approach with several propositions and an illustrative EC example.

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A Posterior Preference Articulation Method to Dual-Response Surface Optimization: Selection of the Most Preferred Solution Using TOPSIS (쌍대반응표면최적화를 위한 사후선호도반영법: TOPSIS를 활용한 최고선호해 선택)

  • Jeong, In-Jun
    • Knowledge Management Research
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    • v.19 no.2
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    • pp.151-162
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    • 2018
  • Response surface methodology (RSM) is one of popular tools to support a systematic improvement of quality of design in the product and process development stages. It consists of statistical modeling and optimization tools. RSM can be viewed as a knowledge management tool in that it systemizes knowledge about a manufacturing process through a big data analysis on products and processes. The conventional RSM aims to optimize the mean of a response, whereas dual-response surface optimization (DRSO), a special case of RSM, considers not only the mean of a response but also its variability or standard deviation for optimization. Recently, a posterior preference articulation approach receives attention in the DRSO literature. The posterior approach first seeks all (or most) of the nondominated solutions with no articulation of a decision maker (DM)'s preference. The DM then selects the best one from the set of nondominated solutions a posteriori. This method has a strength that the DM can understand the trade-off between the mean and standard deviation well by looking around the nondominated solutions. A posterior method has been proposed for DRSO. It employs an interval selection strategy for the selection step. This strategy has a limitation increasing inefficiency and complexity due to too many iterations when handling a great number (e.g., thousands ~ tens of thousands) of nondominated solutions. In this paper, a TOPSIS-based method is proposed to support a simple and efficient selection of the most preferred solution. The proposed method is illustrated through a typical DRSO problem and compared with the existing posterior method.