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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Journal of Intelligence and Information Systems
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Korea Inteligent Information System Society
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Volume 9, Issue 3 - Dec 2003
Volume 9, Issue 2 - Nov 2003
Volume 9, Issue 1 - Jun 2003
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The Study of a Multi-Mobile Agents System for Online Hotel Reservation
Journal of Intelligence and Information Systems , volume 9, issue 1, 2003, Pages 1~21
As electronic commerce(EC) has grown rapidly, agents that work on the behalf of humans on the Internet are being used actively. However, most of the EC agents have some problems. They fail to fully support buyers' decision making behaviors and sellers' information supply activities. Further, they are not suited for mobile computing environment. In this paper, we introduce a Multi-Mobile Agents System(MMAS) that has been developed according to a conceptual framework that corrects the aforementioned problems. Built by using Tokyo IBM ASDK(Aglets Software Development Kit) for the area of hotel reservation, the system consists of buyer- and seller-side agents that interact with each other; buyer-side agents help buyers to make purchasing decisions by collecting and analyzing information through applying a multi-criteria decision making method, while seller-side agents substitute fur sellers by managing databases and providing real-time information to the buyer-side agents. In this system, multiple agents perform their shared tasks at the same time in order to increase efficiency. Users do not have to keep the connection with the system because they are notified when tasks are done.
An Object-Oriented Case-Base Design and Similarity Measures for Bundle Products Recommendation Systems
Journal of Intelligence and Information Systems , volume 9, issue 1, 2003, Pages 23~51
With the recent expansion of internet shopping mall, the importance of intelligent products recommendation agents has been increasing. for the products recommendation, This paper propose case-based reasoning approach, and developed a case-based bundle products recommendation system which can recommend a set of sea food used in family events. To apply CBR approach to the bundle products recommendation, it requires the following 4R steps : \circled1 Retrieval, \circled2 Reuse, \circled3 Revise, \circled4 Retain. To retrieve similar cases from the case-base efficiently, case representation scheme is most important. This paper used OW(Object Modeling Technique) to represent bundle products recommendation cases, and developed a similarity measure method to search similar cases. To measure similarity, we used weight-sum approach basically. Especially This paper propose the meaning and uses of taxonomies for representing case features.
Integrated Procedure of Self-Organizing Map Neural Network and Case-Based Reasoning for Multivariate Process Control
Journal of Intelligence and Information Systems , volume 9, issue 1, 2003, Pages 53~69
Many process variables in modem manufacturing processes have influence on quality of products with complicated relationships. Therefore, it is necessary to control multiple quality variables in order to monitor abnormal signals in the processes. This study proposes an integrated procedure of self-organizing map (SOM) neural network and case-based reasoning (CBR) for multivariate process control. SOM generates patterns of quality variables. The patterns are compared with the reference patterns in order to decide whether their states are normal or abnormal using the goodness-of-fitness test. For validation, it generates artificial datasets consisting of six patterns, normal and abnormal patterns. Experimental results show that the abnormal patterns can be detected effectively. This study also shows that the CBR procedure enables to keep Type 2 error at very low level and reduce Type 1 error gradually, and then the proposed method can be a solution fur multivariate process control.
Aggregating Prediction Outputs of Multiple Classification Techniques Using Mixed Integer Programming
Jo, Hongkyu ; Han, Ingoo ;
Journal of Intelligence and Information Systems , volume 9, issue 1, 2003, Pages 71~89
Although many studies demonstrate that one technique outperforms the others for a given data set, there is often no way to tell a priori which of these techniques will be most effective in the classification problems. Alternatively, it has been suggested that a better approach to classification problem might be to integrate several different forecasting techniques. This study proposes the linearly combining methodology of different classification techniques. The methodology is developed to find the optimal combining weight and compute the weighted-average of different techniques' outputs. The proposed methodology is represented as the form of mixed integer programming. The objective function of proposed combining methodology is to minimize total misclassification cost which is the weighted-sum of two types of misclassification. To simplify the problem solving process, cutoff value is fixed and threshold function is removed. The form of mixed integer programming is solved with the branch and bound methods. The result showed that proposed methodology classified more accurately than any of techniques individually did. It is confirmed that Proposed methodology Predicts significantly better than individual techniques and the other combining methods.
Web-enabled Healthcare System for Hypertension: Hyperlink-based Inference Approach
Song, Yong-Uk ; Ho, Seung-Hee ; Chae, Young-Moon ; Cho, Kyoung-Won ;
Journal of Intelligence and Information Systems , volume 9, issue 1, 2003, Pages 91~107
In the conduct of this study, a web-enabled healthcare system for the management of hypertension was implemented through a hyperlink-based inference approach. The hyperlink-based inference platform was implemented using the hypertext capacity of HTML which ensured accessibility, multimedia facilities, fast response, stability, ease of use and upgrade, and platform independency of expert systems. Many HTML documents, which are hyperlinked to each other based on expert rules, were uploaded beforehand to perform the hyperlink-based inference. The HTML documents were uploaded and maintained automatically by our proprietary tool called the Web-Based Inference System (WeBIS) that supports a graphical user interface (GUI) for the input and edit of decision graphs. Nevertheless, the editing task of the decision graph using the GUI tool is a time consuming and tedious chore when the knowledge engineer must perform it manually. Accordingly, this research implemented an automatic generator of the decision graph for the management of hypertension. As a result, this research suggests a methodology for the development of Web-enabled healthcare systems using the hyperlink-based inference approach and, as an example, implements a Web-enabled healthcare system for hypertension, a platform which performed especially well in the areas of speed and stability.
An Intelligent Agent Based Supply Chain Operation Architecture under Adaptive Relationship between Multiple Suppliers and Customers
Journal of Intelligence and Information Systems , volume 9, issue 1, 2003, Pages 109~123
The relationship between suppliers and customers is treated importantly not only in the traditional business-to-business (BtoB) commerce but also in today's Internet environments. On the one hand, most of Internet-based BtoB commerce services like customer-centric e-procurement, supplier-centric e-sales or intermediary-centric e-marketplace focus mainly on the selection of partners according to bidding, auction, etc. This point may result in the problem of overlooking the relationships between suppliers and customers. To overcome this problem in this paper, an intelligent agents-based supply chain operation architecture is proposed and appraised considering the relationship and its adaptation.
Development of a System for Recognizing Stamp Images
Journal of Intelligence and Information Systems , volume 9, issue 1, 2003, Pages 125~137
In eastern countries stamps have been used more commonly than signatures when approving contracts and documents. Unlike finger prints, stamp images do not share similar patterns to each other and the resolution of stamp images is determined by the input status such as pressure under which stamps are put. This paper discusses the development of a system for recognizing stamp images of Korean or Chinese characters. Recognition of stamp images consists of several steps: acquisition of stamp images from an input device, digitization, contrast stretching, noise removal, and matching. We tested the system on 50 stamp images (20 stamp images of Korean characters, 20 images of Chinese characters, and 10 similar images). There was little difference in discrimination rate between the stamp images of Korean character and those of Chinese characters. 46 stamps images out of 50 were successfully recognized, resulting in 92% discrimination rate. Orientation and pressure under which stamps are put played an important role in determining discrimination rate. Automated stamp image recognition can be made more practical and useful by extending the types of stamp images to ellipses and rectangles and by improving the discrimination rate.
A Study on the Combined Decision Tree(C4.5) and Neural Network Algorithm for Classification of Mobile Telecommunication Customer
Journal of Intelligence and Information Systems , volume 9, issue 1, 2003, Pages 139~155
This paper presents the new methodology of analyzing and classifying patterns of customers in mobile telecommunication market to enhance the performance of predicting the credit information based on the decision tree and neural network. With the application of variance selection process from decision tree, the systemic process of defining input vector's value and the rule generation were developed. In point of customer management, this research analyzes current customers and produces the patterns of them so that the company can maintain good customer relationship and makes special management on the customer who has huh potential of getting out of contract in advance. The real implementation of proposed method shows that the predicted accuracy is higher than existing methods such as decision tree(CART, C4.5), regression, neural network and combined model(CART and NN).
Application of Data mining for improving and predicting yield in wafer fabrication system
Journal of Intelligence and Information Systems , volume 9, issue 1, 2003, Pages 157~177
This paper presents a comprehensive and successful application of data mining methodologies to improve and predict wafer yield in a semiconductor wafer fabrication system. As the wafer fabrication process is getting more complex and the volume of technological data gathered continues to be vast, it is difficult to analyze the cause of yield deterioration effectively by means of statistical or heuristic approaches. To begin with this paper applies a clustering method to automatically identify AUF (Area Uniform Failure) phenomenon from data instead of naked eye that bad chips occurs in a specific area of wafer. Next, sequential pattern analysis and classification methods are applied to and out machines and parameters that are cause of low yield, respectively. Furthermore, radial bases function method is used to predict yield of wafers that are in process. Finally, this paper demonstrates an information system, Y2R-PLUS (Yield Rapid Ramp-up, Prediction, analysis & Up Support), that is developed in order to analyze and predict wafer yield in a korea semiconductor manufacturer.
Transactions Clustering based on Item Similarity
Journal of Intelligence and Information Systems , volume 9, issue 1, 2003, Pages 179~193
Clustering is a data mining method which help discovering interesting data groups in large databases. In traditional data clustering, similarity between objects in the cluster is measured by pairwise similarity of objects. But we devise an advanced measurement called item similarity in this paper, in terms of nature of clustering transaction data and use this measurement to perform clustering. This new algorithm show the similarity by accepting the concept of relationship between different attributes. With this item similarity measurement, we develop an efficient clustering algorithm for target marketing in each group.
Target Marketing using Inverse Association Rule
Journal of Intelligence and Information Systems , volume 9, issue 1, 2003, Pages 195~209
Making traditional plan of target marketing based on association rule has brought restriction to obtain the target of marketing. This paper is to present inverse association rule as a new association rule for target marketing. Inverse association rule does not use information about relation between items that customers purchase, but use information about relation between items that customers do not purchase. By adding inverse association rule to target marketing, we generate new marketing strategy to look for new target of marketing. There are three steps to apply the marketing strategy proposed by this Paper to target marketing. Firstly, a database is converted to an inverse database. Although inverse association rules can be generated from a database, it is easier to explain inverse association rule in an inverse database than in a database. Secondly, association rules and inverse association rules are generated from inverse database. Finally, two types of rules which are created in the previous steps are applied to target marketing. From new marketing rule, this paper is to show direct marketing about target item and indirect marketing about another item associated with target item to sell target item. The reason is that sales of the item associated with target item have an influence on sales of target item.
Collaborative B2B architecture design using Web services
Journal of Intelligence and Information Systems , volume 9, issue 1, 2003, Pages 211~225
This paper aims at the design of collaborative architecture for business to business (B2B) applications based on Web service protocol. As different business processes should be interfaced in the B2B environment collaboration is important fur the success of B2B implementation. For the development tools, XML, Web services and ASP.NET were adopted Web services are emerging to provide a systematic and extensible framework for application-to-application interaction. The Web services framework is divided into three areas; communication protocols, service descriptions and Web discovery. Web services such as SOAP, WSDL and UDDI correspond to the three areas respectively. ASP.NET is utilized which corresponds to the component and service set located in the top layer of .NET. For the service of product category and product details, Web service architecture was implemented based upon the SQL server database.
Using GA based Input Selection Method for Artificial Neural Network Modeling Application to Bankruptcy Prediction
Journal of Intelligence and Information Systems , volume 9, issue 1, 2003, Pages 227~249
Prediction of corporate failure using past financial data is a well-documented topic. Early studies of bankruptcy prediction used statistical techniques such as multiple discriminant analysis, logit and probit. Recently, however, numerous studies have demonstrated that artificial intelligence such as neural networks can be an alternative methodology for classification problems to which traditional statistical methods have long been applied. In building neural network model, the selection of independent and dependent variables should be approached with great care and should be treated as model construction process. Irrespective of the efficiency of a teaming procedure in terms of convergence, generalization and stability, the ultimate performance of the estimator will depend on the relevance of the selected input variables and the quality of the data used. Approaches developed in statistical methods such as correlation analysis and stepwise selection method are often very useful. These methods, however, may not be the optimal ones for the development of neural network model. In this paper, we propose a genetic algorithms approach to find an optimal or near optimal input variables fur neural network modeling. The proposed approach is demonstrated by applications to bankruptcy prediction modeling. Our experimental results show that this approach increases overall classification accuracy rate significantly.
Intelligent Query Processing in Deductive and Object-Oriented Databases
Kim, Yang-Hee ;
Journal of Intelligence and Information Systems , volume 9, issue 1, 2003, Pages 251~267
In order to satisfy the needs of an intelligent information system, it is necessary to have more intelligent query processing in an object-oriented database. In this paper, we present a method to apply intelligent query processing in object-oriented databases using deductive approach. Using this method, we generate intelligent answers to represent the answer-set abstractly for a given query in object-oriented databases. Our approach consists of few stages: rule representation, rule reformation pre-resolution, and resolution. In rule representation, a set of deductive rules is generated based on an object-oriented database schema. In rule reformation, we eliminate the recursion in rules. In pre-resolution, rule transformation is done to get unique intensional literals. In resolution, we use SLD-resolution to generate intensional answers.