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Journal of Intelligence and Information Systems,
Vol. 9, No. 2, November 2003
Recognition of Identifiers from Shipping Container Image by Using Fuzzy Binarization and ART2-based RBF Network
Kwang Baek Kim
Vol. 9, No. 2, Page: 1 ~ 18
Keywords : Container Recognition, Fuzzy Binarization, Contour Tracking, ART2-based RBF Network
Abstract
The automatic recognition of transport containers using image processing is very hard because of the irregular size and position of identifiers, diverse colors of background and identifiers, and the impaired shapes of identifiers caused by container damages and the bent surface of container, etc. We proposed and evaluated the novel recognition algorithm of container identifiers that overcomes effectively the hardness and recognizes identifiers from container images captured in the various environments. The proposed algorithm, first, extracts the area including only all identifiers from container images by using CANNY masking and bi-directional histogram method. The extracted identifier area is binarized by the fuzzy binarization method newly proposed in this paper and by applying contour tracking method to the binarized area, container identifiers which are targets of recognition are extracted. We proposed and applied the ART2-based RBF network for recognition of container identifiers. The results of experiment for performance evaluation on the real container images showed that the proposed algorithm has more improved performance in the extraction and recognition of container identifiers than the previous algorithms.
Self-Evolving Expert Systems based on Fuzzy Neural Network and RDB Inference Engine
Jin Sung Kim
Vol. 9, No. 2, Page: 19 ~ 38
Keywords : Expert systems, Knowledge base, Data mining, Relational database, Relational database, Inference engine, Self-evolving expert systems
Abstract
In this research, we propose the mechanism to develop self-evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most researchers had tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, this approach had some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, knowledge engineers had tried to develop an automatic knowledge extraction mechanism. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference engine. Our proposed mechanism has five advantages. First, it can extract and reduce the specific domain knowledge from incomplete database by using data mining technology. Second, our proposed mechanism can manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it can construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems) module. Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy relationships. Fifth, RDB-driven forward and backward inference time is shorter than the traditional text-oriented inference time.
An Architecture for Certificate and Agent Based E-mailing to Block Spam Mail
SangZo Nam
Vol. 9, No. 2, Page: 39 ~ 50
Keywords : Certificate, Certificate authority, Spam mail
Abstract
Deleting unsolicited email, popularly known as spam mail, is an annoying task for Internet users. Moreover, spam mail causes a variety of social problems. At present, legal restrictions cannot eradicate spam senders. As a result, many technical methods to eliminate spam mail such as spam filtering and online stamps have been introduced. However, the process of blocking spam mail can inadvertently result in suspension of indispensable or beneficial communication. In this paper, we propose a certificate and agent based emailing architecture that can block spam mail, while at the same time approve certified mail. This architecture can be accelerated by synergistic utilization of digital signature and electronic document interchange.
Handling Incomplete Data Problem in Collaborative Filtering System
Hyunju Noh, Minjung Kwak, and Ingoo Han
Vol. 9, No. 2, Page: 51 ~ 63
Keywords : Multiple Imputation, Collaborative Filtering, Incomplete data
Abstract
Collaborative filtering is one of the methodologies that are most widely used for recommendation system. It is based on a data matrix of each customer's preferences of products. There could be a lot of missing values in such preference data matrix. This incomplete data is one of the reasons to deteriorate the accuracy of recommendation system. There are several treatments to deal with the incomplete data problem such as case deletion and single imputation. Those approaches are simple and easy to implement but they may provide biased results. Multiple imputation method imputes m values for each missing value. It overcomes flaws of single imputation approaches through considering the uncertainty of missing values. The objective of this paper is to suggest multiple imputation-based collaborative filtering approach for recommendation system to improve the accuracy in prediction performance. The experimental works show that the proposed approach provides better performance than the traditional Collaborative filtering approach, especially in case that there are a lot of missing values in dataset used for recommendation system.
Successful ERP Operations: Process Integration Perspectives and an Agent-Based Support System
Kwangho Park
Vol. 9, No. 2, Page: 65 ~ 85
Keywords : ERP Operations, Agent System, Decision Support System, Process Integration
Abstract
Any ERP system pushes a company toward full process integration and solves the fragmentation of information. However, the tight process integration can propagate and magnify mistakes made in one department into the other departments in real time. Thus, it can be posited that a central support system for the coordination can help ERP users and administrators dig out problems, take care of tedious validation and verification, and maintain process integration of ERP with great consistency. This paper proposes an agent-based ERP operations support system (EOSS) that aims at achieving and maintaining process integration of ERP at the highest level possible. With EOSS, the process integrity is monitored, with anomalies prevented as early as possible and repaired as precisely as possible.
Fuzzy based Intelligent Expert Search for Knowledge Management Systems
Kun Woo Yang, and Soon Young Huh
Vol. 9, No. 2, Page: 87 ~ 100
Keywords : expert search, knowledge management, text categorization
Abstract
In managing organizational tacit knowledge, recent researches have shown that it is more applicable in many ways to provide expert search mechanisms in KMS to pinpoint experts in the organizations with searched expertise. In this paper, we propose an intelligent expert search framework to provide search capabilities for experts in similar or related fields according to the user′s information needs. In enabling intelligent expert searches, Fuzzy Abstraction Hierarchy (FAH) framework has been adopted, through which finding experts with similar or related expertise is possible according to the subject field hierarchy defined in the system. To improve FAH, a text categorization approach called Vector Space Model is utilized. To test applicability and practicality of the proposed framework, the prototype system, "Knowledge Portal for Researchers in Science and Technology" sponsored by the Ministry of Science and Technology (MOST) of Korea, was developed.
Building Intelligent User Interface Agent for Semantically Reformulating User Query in Medicine
JungJin Yang, ChaeMyung Lim, SungJoon Chu, DongHoon Lee, DuckWhan Park, and TaeYong Park
Vol. 9, No. 2, Page: 101 ~ 119
Keywords : Ontology, Bioinformatics, Semantic Web and Agent Integration
Abstract
Achieving the beneficiary goal of recent discovery in human genome project still needs a way to retrieve and analyze the exponentially expanding bio-related information. Research on bio-related fields naturally applies knowledge discovered to the current problem and make inferences to extract new information where shared concepts and data containing information need to be defined and used in a coherent way. In such a professional domain, while the need to help users reduce their work and to improve search results has been emerged, methods for systematic retrieval and adequate exchange of relevant information are still in their infancy. The design of our system aims at improving the quality of information retrieval in a professional domain by utilizing both corpus-based and concept-based ontology. Meta-rules of helping users to make an adequate query are formed into an ontology in the domain. The integration of those knowledge permits the system to retrieve relevant information in a more semantic and systematic fashion. This work mainly describes the query models with details of GUI and a secondary query generation of the system.
A Case Based e-Mail Response System for Customer Support
Young Suk Yoon, Jae Kwang Lee, and Chang Hee Han
Vol. 9, No. 2, Page: 121 ~ 133
Keywords : customer support, e-mail response, case based reasoning
Abstract
Due to the rapid growth of Internet, means of communication with customers in a traditional customer support environment such as telephone calls are being replaced by mainly e-mail in a Web-based customer support system. Although such a Web-based support is efficient and promises potential benefits for firms, including reduced transaction costs, reduced time, and high quality of support, there are some difficulties associated with responding to many types of customer's inbound e-mails appropriately. As many types of e-mail are received, considerable attention is being paid to methods for increasing the efficiency of managing and responding e-mails. This research proposes an intelligent system for managing customer's inbound e-mails in organizations by applying case based reasoning technique for responding to various customers' inbound e-mails more effectively. In this approach, a case is represented as a frame-typed data structure corresponding to an inbound e-mail, keywords, and its reply e-mail. In the retrieval procedure, keywords and affinity set is developed to index a case, and then the case is represented as a vector, a case vector. Also, cosines value is calculated to measure the similarity between a new inbound e-mail and the cases in the case base. In the adaptation procedure, we provide several adaptation strategies to adapt and modify the retrieved case. The strategies guide to make an outbound e-mail using product databases, databases for customer support, etc. Additionally, the Web-based system architecture is proposed to implement our methodology. The proposed methodology and system will be helpful for developing more efficient Web-based customer support.
Mining Association Rules of Credit Card Delinquency of Bank Customers in Large Databases
Young-Chan Lee, and Soo-Il Shin
Vol. 9, No. 2, Page: 135 ~ 154
Keywords : Association rules, credit scoring system
Abstract
Credit scoring system (CSS) starts from an analysis of delinquency trend of each individual or industry. This paper conducts a research on credit card delinquency of bank customers as a preliminary step for building effective credit scoring system to prevent excess loan or bad credit status. To serve this purpose, we use association rules as a rule generating data mining technique. Specifically, we generate sets of rules of customers who are in bad credit status because of delinquency by association rule mining. We expect that the sets of rules generated by association rule mining could act as an estimator of good or bad credit status classifier and basic component of early warning system.
A Design of Multi-Agent Framework to Develop Negotiation Systems
Hyung Rim Choi, Hyun Soo Kim, Soon Goo Hong, Young Jae Park, Yong Sung Park, and Moo Hong Kang
Vol. 9, No. 2, Page: 155 ~ 169
Keywords : Negotiation, Multi-Agent Framework
Abstract
A multi-agent technology has emerged as new paradigms that can flexibly and promptly cope with various environmental changes and complex problems. Accordingly, many studies have been carried out to establish multi-agent systems in an effort to solve dynamic problems in many fields. However, most previous research on the multi-agent frameworks aimed at, on the behalf of a user, exchanging and sharing information among agents, reusing agents, and suggesting job cooperation in order to integrate and assimilate heterogeneous agents. That is, their frameworks mainly focused on the basic functions of general multi-agents. Therefore, they are not suitable to the development of the proper system for a specific field such as a negotiation. The goal of this research is to design a multi-agent framework for the negotiation system that supports the evaluation of the negotiation messages, management of the negotiation messages, and message exchanges among the negotiation agents.
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