• Proceedings of the Korean Information Science Society Conference
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• 2000.10c
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• pp.6-8
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• 2000

본 연구에서는 자원제약이 존재할 때의 스케듈링 문제인 자원제약에서 리스트 스케듈링 방법을 이용했으며, 기존의 리스트 스케듈링 기법이 모든 우선순위 함수를 산출한 후, 이에 근거에 스케듈링을 하는 반면, Forward 스케듈링 기법은 스케듈링 과정 내에서 필요한 경우에만 연산의 우선순위 함수를 산출하여 이를 이용하는 방식을 택했다.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.4
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• pp.745-750
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• 2009

The goal of this study is to examine on reasoning and search for construction of diagnosis ontology as a knowledge base of diagnosis expert system in oriental medicine. Expert system is a field of artificial intelligence. It is a system to acquire information with diverse reasoning methods after putting expert's knowledge in computer systematically. A typical model of expert system consists of knowledge base and reasoning & explanatory structure offering conclusion with the knowledge. To apply ontology as knowledge base to expert system practically, consideration on reasoning and search should be together. Therefore, this study compared and examined reasoning, search with diagnosis process in oriental medicine. Reasoning is divided into Rule-based reasoning and Case-based reasoning. The former is divided into Forward chaining and Backward chaining. Because of characteristics of diagnosis, sometimes Forward chaining or backward chaining are required. Therefore, there are a lot of cases that Hybrid chaining is effective. Case-based reasoning is a method to settle a problem in the present by comparing with the past cases. Therefore, it is suitable to diagnosis fields with abundant cases. Search is sorted into Breadth-first search, Depth-first search and Best-first search, which have respectively merits and demerits. To construct diagnosis ontology to be applied to practical expert system, reasoning and search to reflect diagnosis process and characteristics should be considered.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.17-29
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• 2007

Inference engine that performs the brain of software agent in next generation's web with various standards based on standard language of the web, XML has to understand SWRL (Semantic Web Rule Language) that is a language to express the rule in the Semantic Web. In this research, we want to develop a forward inference engine, SMART-F (SeMantic web Agent Reasoning Tools-Forward chaining inference engine) that uses SWRL as a rule express method, and OWL as a fact express method. In the traditional inference field, the Rete algorithm that improves effectiveness of forward rule inference by converting if-then rules to network structure is often used for forward inference. To apply this to the Semantic Web, we analyze the required functions for the SWRL-based forward inference, and design the forward inference algorithm that reflects required functions of next generation's Semantic Web deducted by Rete algorithm. And then, to secure each platform's independence and portability in the ubiquitous environment and overcome the gap of performance, we developed management tool of fact and rule base and forward inference engine. This is compatible with fact and rule base of SMART-B that was developed. So, this maximizes a practical use of knowledge in the next generation's Web environment.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.121-130
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• 1999

The objective of this paper is to apply Extended AND-OR Graph (EAOG)-related techniques to extract knowledge from a specific problem-domain and perform analysis in complicated decision making area. Expert systems use expertise about a specific domain as their primary source of solving problems belonging to that domain. However, such expertise is complicated as well as uncertain, because most knowledge is expressed in causal relationships between concepts or variables. Therefore, if expert systems can be used effectively to provide more intelligent support for decision making in complicated specific problems, it should be equipped with real-time inference mechanism. We develop two kinds of EAOG-driven inference mechanisms(1) EAOG-based forward chaining and (2) EAOG-based backward chaining. and The EAOG method processes the following three characteristics. 1. Real-time 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 backward chaining which is mutually exclusive in terms of logical process and computational efficiency. However, the proposed EAOG inference mechanism is generically bi-directional without loss of both speed and efficiency.

• Journal of KIISE:Databases
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• v.36 no.2
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• pp.123-138
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• 2009

In recent years, the web services composition search has become an issue of great interest. The web services composition search is the process of integrating individual web services to yield desired behavior. Through the web services composition search, more sophisticated functionalities can be provided. Current solutions can be classified into three main classes: forward chaining approach, backward chaining approach and two-phase approach. However one-way chaining approaches, such as forward chaining approach and backward chaining approach have limitations of searching irrelevant web services. And two-phase approach has limitations of including redundant web services. In this paper, we propose an unredundant web services composition search based on the two-phase algorithm. The algorithm consists of a forward phase and a backward phase. In the forward phase, the candidate web services participating composition will be found efficiently by searching the Link Index. In the backward phase, unredundant web services compositions will be generated from candidate web services by using the Token Manager. The experimental results show that our proposed algorithm is more efficient than one-way chaining approaches. The experimental results also show that our algorithm can provide more solutions than previous two-phase approach and is comparable to previous one in execution time.

• Therapeutic Science for Rehabilitation
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• v.13 no.1
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• pp.87-97
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• 2024

Objective : This study aimed to acquire activities of daily living (ADL) skills through activity analysis and forward chaining in children with developmental disabilities. Methods : In this study, the performance of children with developmental disabilities was guided stepwise using a changing criterion design. The intervention was conducted in forward chaining after the therapist analyzed the activities of three tasks (shoes, shorts, and short-sleeved T-shirts) set as the Canadian Occupational Performance Measure (COPM). The performance rate at each stage of the three tasks was used as an independent variable, and COPM performance and satisfaction scores before and after the intervention were set as dependent variables. Results : The task performance rates of children wearing shoes, shorts, and short-sleeved T-shirts improved over time. Even at home, the scores for performance and satisfaction of all three tasks increased. Conclusion : Hopefully, activity analysis and behavioral chaining methods will be used not only for ADL but also for various tasks in children with developmental disabilities who have difficulty acquiring tasks.

• IE interfaces
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• v.17 no.1
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• pp.13-21
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• 2004

In this study, the prototype of a system for checking risk-factor of NC machine is proposed. The proposed system can get the risk-related information by monitoring the status of real-time processes of NC machines. Using the information, the accidents can be prevented by the background process of an expert system tool. This paper consists of 2 parts: (1) the method for gathering data and definition of the risk-related factors of NC machines and (2) the procedure for finding the proper actions by using the forward chaining of a rule-base. Proposed system is implemented with C++ language under MS-windows.

• Journal of KIISE:Databases
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• v.33 no.2
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• pp.151-162
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• 2006

RDF Semantics, one of W3C Recommendations, provides the RDFS entailment rules, which are used for the RDFS inference. Sesame, which is well known RDF repository, supports the RDBMS-based RDFS inference using the forward-chaining strategy. Since inferencing in the forward-chaining strategy is performed in the data loading time, the data loading time in Sesame is slow down be inferencing. In this paper, we propose the order scheme for applying the RDFS entailment rules to improve inference performance. The proposed application order makes the inference process terminate without repetition of the process for most cases and guarantees the completeness of inference result. Also the application order helps to reduce redundant results during the inference by predicting the results which were made already by previously applied rules. In this paper, we show that our approaches can improve the inference performance with comparisons to the original Sesame using several real-life RDF datasets.

• Journal of Internet Computing and Services
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• v.9 no.3
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• pp.79-90
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• 2008

This paper introduces how we have designed and implemented an efficient starting line-up system of professional baseball players, using the forward chaining technology which is an expert system technology. The knowledge base adopted holds 286 players and 148 evaluation Items. Each player's competitiveness is measured as a numerical value in points through 2 different phases. The 1st phase point represents the static information of the target player and the 2nd his dynamic information. This paper gets a representative value of the player, which is used as the basis on which an efficient line-up system in views of both game environments and counterparts is constructed.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.353-359
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• 1999

We present a matrix-based inference algorithm suitable for electronic commerce applications. For this purpose, an Extended AND-OR Graph (EAOG) was developed with the intention that fast inference process is enabled within the electronic commerce situations. The proposed EAOG inference mechanism has the following three characteristics. 1. Real-time 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 backward chaining which is mutually exclusive in terms of logical process 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.