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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 & Issues
Volume 15, Issue 4 - Dec 2009
Volume 15, Issue 3 - Sep 2009
Volume 15, Issue 2 - Jun 2009
Volume 15, Issue 1 - Mar 2009
Selecting the target year
Evaluation of Web Service Similarity Assessment Methods
Hwang, You-Sub ;
Journal of Intelligence and Information Systems , volume 15, issue 4, 2009, Pages 1~22
The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component based software development to promote application interaction and integration both within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web service repositories not only be well-structured but also provide efficient tools for developers to find reusable Web service components that meet their needs. As the potential of Web services for service-oriented computing is being widely recognized, the demand for effective Web service discovery mechanisms is concomitantly growing. A number of techniques for Web service discovery have been proposed, but the discovery challenge has not been satisfactorily addressed. Unfortunately, most existing solutions are either too rudimentary to be useful or too domain dependent to be generalizable. In this paper, we propose a Web service organizing framework that combines clustering techniques with string matching and leverages the semantics of the XML-based service specification in WSDL documents. We believe that this is one of the first attempts at applying data mining techniques in the Web service discovery domain. Our proposed approach has several appealing features : (1) It minimizes the requirement of prior knowledge from both service consumers and publishers; (2) It avoids exploiting domain dependent ontologies; and (3) It is able to visualize the semantic relationships among Web services. We have developed a prototype system based on the proposed framework using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web service registries. We report on some preliminary results demonstrating the efficacy of the proposed approach.
Improvement of Network Intrusion Detection Rate by Using LBG Algorithm Based Data Mining
Park, Seong-Chul ; Kim, Jun-Tae ;
Journal of Intelligence and Information Systems , volume 15, issue 4, 2009, Pages 23~36
Network intrusion detection have been continuously improved by using data mining techniques. There are two kinds of methods in intrusion detection using data mining-supervised learning with class label and unsupervised learning without class label. In this paper we have studied the way of improving network intrusion detection accuracy by using LBG clustering algorithm which is one of unsupervised learning methods. The K-means method, that starts with random initial centroids and performs clustering based on the Euclidean distance, is vulnerable to noisy data and outliers. The nonuniform binary split algorithm uses binary decomposition without assigning initial values, and it is relatively fast. In this paper we applied the EM(Expectation Maximization) based LBG algorithm that incorporates the strength of two algorithms to intrusion detection. The experimental results using the KDD cup dataset showed that the accuracy of detection can be improved by using the LBG algorithm.
Product Life Cycle Based Service Demand Forecasting Using Self-Organizing Map
Chang, Nam-Sik ;
Journal of Intelligence and Information Systems , volume 15, issue 4, 2009, Pages 37~51
One of the critical issues in the management of manufacturing companies is the efficient process of planning and operating service resources such as human, parts, and facilities, and it begins with the accurate service demand forecasting. In this research, service and sales data from the LCD monitor manufacturer is considered for an empirical study on Product Life Cycle (PLC) based service demand forecasting. The proposed PLC forecasting approach consists of four steps : understanding the basic statistics of data, clustering models using a self-organizing map, developing respective forecasting models for each segment, comparing the accuracy performance. Empirical experiments show that the PLC approach outperformed the traditional approaches in terms of root mean square error and mean absolute percentage error.
Performance Evaluation of Shape Descriptors for Gait Analysis Based on Silhouette Sequence
Kim, Seon-Jong ;
Journal of Intelligence and Information Systems , volume 15, issue 4, 2009, Pages 53~64
This paper presents a performance evaluation of shape descriptors for gait analysis in case of silhouette sequence images. We used moment descriptors(MD), Fourier descriptors(FD) and Zernike descriptors(ZD) as a shape descriptor. To evaluate their performance, we firstly defined the performance index, that is, AI(asymmetry index) and PI(periodic index) based on the periodic property of the gait images. This is why they are represented by periodic parameters due to periodic gait images. This index means that how the shape is represented periodically. According to these indexes, we evaluated the data sets with periodic images, downloaded from internet. The results showed that Zernike descriptors had better performance of AI = 1.09 and PI = 2.21 than others. And in case of FD and ZD, it's efficient to implement the gait analysis with 5~10 parameters.
The Design of Intelligent Agent for Personal Finance Management System on Ubiquitous Environments
Shin, Kyung-Shik ; Kim, Nam-Hee ;
Journal of Intelligence and Information Systems , volume 15, issue 4, 2009, Pages 65~78
The rapid changes of financial environment have increased the need and demand for personal financial advisory service from financial experts. In particular, as the individual customers want to get more customized financial services, the financial institutions created the private banking (PB) sector and have constantly expanded their PB services. However, it remains still problematic that the private banking system requires high costs so that the number of eligible customers who can have proper PB services is quite limited. To solve this problem, we propose an intelligent agent that can provides specialized and customized personal financial advisory services to the customers with low costs. The proposed agent systemizes and structures the information and knowledge of financial experts in private banking services so that individual customers can easily access to high-quality PB services when they need. On the first attempt we develop a framework of U-smart PB, an intelligent agent for personal financial management based on different scenarios related to personal financial decisions, and derive its core services. This system not only provides information simply, but also proposes to support personal investment decisions technically as an intelligent agent that embodies real-time customized financial management in a ubiquitous environment, regardless of time and place.
An Empirical Study on the relevance of Web Traffic for Valuation of Internet Companies
Yi, Sung-Wook ; Hwang, Seung-June ;
Journal of Intelligence and Information Systems , volume 15, issue 4, 2009, Pages 79~98
Web traffic is becoming an important indicator to make inferences about internet companies' future prospects so that traditional firm valuation methods need to be modified to integrate the ideas of web traffic information as a major asset of internet companies. It is because web traffic is a measure of attracting visitors to firm's web site and is the basis for internet companies' marketing expenditure and customer acquisition and retention. Also the web traffic represents the internet companies' technological advances and marketability. The major purpose of this study is to show the relevance of web traffic for valuation of internet companies. For this, we test hypothesis with the firm's web traffic and financial data using the analysis model of Hand(2000a) derived from the log-linear model introduced by Ye and Finn(1999). Test results show that the web traffic, more specifically the number of unique visitors, visits, and page views are all positively related to the firm's value. This implies that the web traffic information should be considered as one of the important non-financial indicator for the internet firm valuation.
Integrated Corporate Bankruptcy Prediction Model Using Genetic Algorithms
Ok, Joong-Kyung ; Kim, Kyoung-Jae ;
Journal of Intelligence and Information Systems , volume 15, issue 4, 2009, Pages 99~121
Recently, there have been many studies that predict corporate bankruptcy using data mining techniques. Although various data mining techniques have been investigated, some researchers have tried to combine the results of each data mining technique in order to improve classification performance. In this study, we classify 4 types of data mining techniques via their characteristics and select representative techniques of each type then combine them using a genetic algorithm. The genetic algorithm may find optimal or near-optimal solution because it is a global optimization technique. This study compares the results of single models, typical combination models, and the proposed integration model using the genetic algorithm.
Evaluation of Interpretability for Generated Rules from ANFIS
Song, Hee-Seok ; Kim, Jae-Kyeong ;
Journal of Intelligence and Information Systems , volume 15, issue 4, 2009, Pages 123~140
Fuzzy neural network is an integrated model of artificial neural network and fuzzy system and it has been successfully applied in control and forecasting area. Recently ANFIS(Adaptive Network-based Fuzzy Inference System) has been noticed widely among various fuzzy neural network models because of outstanding performance of control and forecasting accuracy. ANFIS has capability to refine its fuzzy rules interactively with human expert. In particular, when we use initial rule structure for machine learning which is generated from human expert, it is highly probable to reach global optimum solution as well as shorten time to convergence. We propose metrics to evaluate interpretability of generated rules as a means of acquiring domain knowledge and compare level of interpretability of ANFIS fuzzy rules to those of C5.0 classification rules. The proposed metrics also can be used to evaluate capability of rule generation for the various machine learning methods.
Framework for Information Integration and Customization Using Ontology and Case-based Reasoning
Lee, Hyun-Jung ; Sohn, M-Ye ;
Journal of Intelligence and Information Systems , volume 15, issue 4, 2009, Pages 141~158
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.
A Network Approach to Derive Product Relations and Analyze Topological Characteristics
Kim, Hyea-Kyeong ; Kim, Jae-Kyeong ; Chen, Qiu-Yi ;
Journal of Intelligence and Information Systems , volume 15, issue 4, 2009, Pages 159~182
We construct product networks from the retail transaction dataset of an off-line department store. In the product networks, nodes are products, and an edge connecting two products represents the existence of co-purchases by a customer. We measure the quantities frequently used for characterizing network structures, such as the degree centrality, the closeness centrality, the betweenness centrality and the centralization. Using the quantities, gender, age, seasonal, and regional differences of the product networks were analyzed and network characteristics of each product category containing each product node were derived. Lastly, we analyze the correlations among the three centrality quantities and draw a marketing strategy for the cross-selling.
Social Network Analysis for New Product Recommendation
Cho, Yoon-Ho ; Bang, Joung-Hae ;
Journal of Intelligence and Information Systems , volume 15, issue 4, 2009, Pages 183~200
Collaborative Filtering is one of the most used recommender systems. However, basically it cannot be used to recommend new products to customers because it finds products only based on the purchasing history of each customer. In order to cope with this shortcoming, many researchers have proposed the hybrid recommender system, which is a combination of collaborative filtering and content-based filtering. Content-based filtering recommends the products whose attributes are similar to those of the products that the target customers prefer. However, the hybrid method is used only for the limited categories of products such as music and movie, which are the products whose attributes are easily extracted. Therefore it is essential to find a more effective approach to recommend to customers new products in any category. In this study, we propose a new recommendation method which applies centrality concept widely used to analyze the relational and structural characteristics in social network analysis. The new products are recommended to the customers who are highly likely to buy the products, based on the analysis of the relationships among products by using centrality. The recommendation process consists of following four steps; purchase similarity analysis, product network construction, centrality analysis, and new product recommendation. In order to evaluate the performance of this proposed method, sales data from H department store, one of the well.known department stores in Korea, is used.
Robust Audio Copyright Protection Technology to the Time Axis Attack
Bae, Kyoung-Yul ;
Journal of Intelligence and Information Systems , volume 15, issue 4, 2009, Pages 201~212
Even though the spread spectrum method is known as most robust algorithm to general attacks, it has a drawback to the time axis attack. In this paper, I proposed a robust audio copyright protection algorithm which is robust to the time axis attack and has advantages of the spread spectrum method. Time axis attack includes the audio length variation attack with same pitch and the audio frequency variation attack. In order to detect the embedded watermark by the spread spectrum method, the detection algorithm should know the exact rate of the time axis attack. Even if there is a method to know the rate, it needs heavy computational resource and it is not possible to implement. In this paper, solving this problem, the audio signal is transformed into time-invariant domain, and the spread spectrum watermark is embedded into the audio in the domain. Therefore the proposed algorithm has the advantages of the spread spectrum method and it is also robust to the time axis attack. The time-invariant domain process is that the audio is arranged by log scale time axis, and then, the Fourier transform is taken to the audio in the log scale time axis. As a result, the algorithm can get the time-invariant watermark signal.
Real-Time Scheduling System Re-Construction for Automated Manufacturing in a Korean 300mm Wafer Fab
Choi, Seong-Woo ; Lee, Jung-Seung ;
Journal of Intelligence and Information Systems , volume 15, issue 4, 2009, Pages 213~224
This paper describes a real-time scheduling system re-construction project for automated manufacturing at a 300mm wafer fab of Korean semiconductor manufacturing company. During executing this project, for each main operation such as clean, diffusion, deposition, photolithography, and metallization, each adopted scheduling algorithm was developed, and then those were implemented in a real-time scheduling system. In this paper, we focus on the scheduling algorithms and real-time scheduling system for clean and diffusion operations, that is, a serial-process block with the constraint of limited queue time and batch processors. After this project was completed, the automated manufacturing utilizations of clean and diffusion operations became around 91% and 83% respectively, which were about 50% and 10% at the beginning of this project. The automated manufacturing system reduces direct operating costs, increased throughput on the equipments, and suggests continuous and uninterrupted processings.