• Journal of Intelligence and Information Systems
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• v.1 no.1
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• pp.91-109
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• 1995

This paper compared four knowledge acquisition methods (namely, neural network, case-based reasoning, discriminant analysis, and covariance structure modeling) for allergic rhinitis. The data were collected from 444 patients with suspected allergic rhinitis who visited the Otorlaryngology Deduring 1991-1993. Among four knowledge acquisition methods, the discriminant model had the best overall diagnostic capability (78%) and the neural network had slightly lower rate(76%). This may be explained by the fact that neural network is essentially non-linear discriminant model. The discriminant model was also most accurate in predicting allergic rhinitis (88%). On the other hand, the CSM had the lowest overall accuracy rate (44%) perhaps due to smaller input data set. However, it was most accuate in predicting non-allergic rhinitis (82%).

• The Transactions of the Korea Information Processing Society
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• v.7 no.5S
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• pp.1649-1656
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• 2000

In this paper, We describe a design of sales agent for support for negotiation during sales support on the Internet within Case-Based Reasoning (CBR) solutions. First, We propose an multi-agent system which can effectively search complex product on the WWW. And we represent databases and case-bases and propose a CBR cycle for sales agent. We then implement some of them in a prototype for a sales agent and a case study is shown where preliminary approaches are used to negotiate with a customer about his demands and available produucts in a CBR-based Electronic Commerce solution.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.183-190
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• 2009

The core technique of ubiquitous computing is the context aware computing and the context aware technique is more like software so the important research work is to develop the core engines first and the adapted device for the engines. When ubiquitous computing era comes, the current existing internet shopping mall, the form of searching the direct goods and ordering the goods by the customers evolves and develops the form of system that recommends the goods by the search engine which combined with the input data and technique of case based reasoning and intelligent agent that is based on the context aware technique. In this paper, search engine which is based on the case based reasoning and intelligent agent is designed and the prototype is implemented to be adapted to the internet fashion expert shopping mall.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1693-1705
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• 2013

To restore old aqueduct in Korea which is a irrigation bridge to supply water in paddy field area, it is needed to estimate approximate costs of restoration because the basic design for estimation of construction costs is often ruled out in current system. In this paper, estimating models of construction costs were developed on the basis of performance data for restoration of RC aqueduct bridges since 2003. The regression analysis (RA) model and case-based reasoning (CBR) model for the estimation of construction costs were developed respectively. Error rate of simple RA model was lower than that of multiple RA model. CBR model using genetic algorithm (GA) has been applied in the estimation of construction costs. In the model three factors like attribute weight, attribute deviation and rank of case similarity were optimized. Especially, error rate of estimated construction costs decreased since limit ranges of the attribute weights were applied. The results showed that error rates between RA model and CBR models were inconsiderable statistically. It is expected that the proposed estimating method of approximate costs of aqueduct restoration will be utilized to support quick decision making in phased rehabilitation project.

• Journal of Intelligence and Information Systems
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• v.15 no.4
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• pp.141-158
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• 2009

The requirements of knowledge customization have increased as information resources have become more various and the numbers of the resources are increased. Even if the method for collecting the information has improved like Really Simple Syndication (RSS), information users are still struggling for extracting and customizing the required information through the Web. To reduce the burden, we offer the dynamic knowledge customization framework by using ontology-based CBR. The framework consisting of three phases is comprised of the conversion phase of web information as a machine-accessible case, the extraction phase to find a case appropriate for information users' requirements, and the case customization phase to create knowledge depending on information user's requirements. Newly, the dynamic and intensity-based similarity is adopted to support timely dynamic change of users' requirements. The framework has adopted to create traveler's knowledge to the level users wanted.

• Journal of Information Technology Application
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• v.1
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• pp.99-127
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• 1999

Under the concept of global economy, the enterprises are assigning design and production environments around the world in different areas. A serious problem of information exchange emerges as companies use traditional hardware and very distinct softwares appropriate to their field of expertise. To overcome the decreased productivity due to the interruption of information, the concept of simultaneous engineering and concurrent design becomes very significant. In this article, an agent-based ship design system is developed in order to support a cooperation in distributed ship design environments. Above all, the conflicts that occur in the middle of knowledge sharing in the system must be resolved. An approach to do this is the case-based conflict resolution strategy formulated to resolve current conflict on the basis of previous resolved similar cases in agent-based collaborative design system environments. To do this conflict cases that occur in initial ship design stage are extracted. On the basis of the extracted cases, case-base is constructed. In addition conflict resolution handler located in the facilitator is developed to treat conflict problems effectively by reasoning of the case-base and thus presenting an appropriate solution. The validation of developed case-based conflict resolution strategy is evaluated by applying to collaborative design process in initial ship design stage, especially the machinery outfitting design, the preliminary design, the hullform design, and the structural design. Through the help of the cooperation of the design agents, the facilitator, the conflict resolution handler, and the case-based system, a designer can be supported effectively in his/her decision-making based on the previous cases resolved similarly.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.47-61
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• 2001

Lazy loaming methods including CBR have relative advantages in comparison with eager loaming methods such as artificial neural networks and decision trees. However, they are very sensitive to irrelevant features. In other words, when there are irrelevant features, larry learning methods have difficulty in comparing cases. Therefore, their performance can be degraded significantly. To overcome this disadvantage, feature weighting methods for lazy loaming methods have been studied. Most of the existing researches, however, were focused on global feature weighting. In this research, we propose a new local feature weighting method, which we shall call CBDFW. CBDFW stores classification performance of randomly generated feature weight vectors. Then, given a new query case, CBDFW retrieves the successful feature weight vectors and designs a feature weight vector fur the query case. In the test on credit evaluation domain, CBDFW showed better classification accuracy when compared to the results of previous researches.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.1
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• pp.109-141
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• 1998

Many processes in the industrial realm exhibit sstochastic and nonlinear behavior. Consequently, an intelligent system must be able to nonlinear production processes as well as probabilistic phenomena. In order for a knowledge based system to control a manufacturing processes as well as probabilistic phenomena. In order for a knowledge based system to control manufacturing process, an important capability is that of prediction : forecasting the future trajectory of a process as well as the consequences of the control action. This paper examines the robustness of data mining tools under varying levels of noise while predicting nonlinear processes, includinb chaotic behavior. The evaluated models include the perceptron neural network using backpropagation (BPN), the recurrent neural network (RNN) and case based reasoning (CBR). The concepts are crystallized through a case study in predicting a chaotic process in the presence of various patterns of noise.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.1009-1016
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• 2002

We design and implement a new case-based recommender system using implicit rating information for a digital content site. Our system consists of the User Profile Generation module, the Similarity Evaluation and Recommendation module, and the Personalized Mailing module. In the User Profile Generation Module, we define intra-attribute and inter-attribute weight deriver from own's past interests of a user stored in the access logs to extract individual preferences for a content. A new similarity function is presented in the Similarity Evaluation and Recommendation Module to estimate similarities between new items set and the user profile. The Personalized Mailing Module sends individual recommended mails that are transformed into platform-independent XML document format to users. To verify the efficiency of our system, we have performed experimental comparisons between the proposed model and the collaborative filtering technique by mean absolute error (MAE) and receiver operating characteristic (ROC) values. The results show that the proposed model is more efficient than the traditional collaborative filtering technique.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.119-139
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• 2002

In electronic catalogs, each item is represented as an independent unit while the parts of the item can be composed of a higher level of functionality. Thus, the search for this kind of product database is limited to the retrieval of most similar standard commodities. However, many industrial products need to configure optional parts to fulfill the required specifications. Since there are many paths in finding the required specifications, we need to develop a search system via the configuration process. In this system, we adopt a two-phased approach. The first phase finds the most similar template, and the second phase adjusts the template specifications toward the required set of specifications by the Constraint and Rule Satisfaction Problem approach. There is no guarantee that the most similar template can find the most desirable configuration. The search system needs backtracking capability, so the search can stop at a satisfied local optimal satisfaction. This framework is applied to the configuration of computers and peripherals. Template-based reasoning is basically the same as case-based reasoning. The required set of specifications is represented by a list of criteria, and matched with the product specifications to find the closest ones. To measure the distance, we develop a thesaurus of values, which can identify the meaning of numbers, symbols, and words. With this configuration, the performance of the search by configuration algorithm is evaluated in terms of feasibility and admissibility.