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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 8, Issue 2 - Dec 2002
Volume 8, Issue 1 - Jun 2002
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Moving Object Tracking Using Co-occurrence Features of Objects
Kim, Seongdong ; Seongah Chin ; Moonwon Choo ;
Journal of Intelligence and Information Systems , volume 8, issue 2, 2002, Pages 1~13
In this paper, we propose an object tracking system which can be convinced of moving area shaped on objects through color sequential images, decided moving directions of foot messengers or vehicles of image sequences. In static camera, we suggests a new evaluating method extracting co-occurrence matrix with feature vectors of RGB after analyzing and blocking difference images, which is accessed to field of camera view for motion. They are energy, entropy, contrast, maximum probability, inverse difference moment, and correlation of RGB color vectors. we describe how to analyze and compute corresponding relations of objects between adjacent frames. In the clustering, we apply an algorithm of FCM(fuzzy c means) to analyze matching and clustering problems of adjacent frames of the featured vectors, energy and entropy, gotten from previous phase. In the matching phase, we also propose a method to know correspondence relation that can track motion each objects by clustering with similar area, compute object centers and cluster around them in case of same objects based on membership function of motion area of adjacent frames.
An Artificial Intelligence-based Data Mining Approach to Extracting Strategies for Reducing the Churning ]date in Credit Card Industry
Journal of Intelligence and Information Systems , volume 8, issue 2, 2002, Pages 15~35
Data mining has received a lot of attention from practitioners. That is partly because it allows company to extract a set of useful knowledge about customers from database, thereby retaining current customers and magneting potential customers. This logic is especially essential in the field of credit card industry, where just 5% increase of number of customers is hewn to cause 120% increase in profit. The problem is how to retain current customers and even make them more loyal to company. However, previous studies lacked proposing extensive strategies of reducing the churning rate. In this sense, this study attempts to suggest such strategies by applying neural network, logistic regression, and C5.0 techniques to credit card data. We used a real data set of four years from 1997 to 2000, which were gathered from a credit card company. Experimental results revealed that our approach could yield robust strategies for retaining customers by reducing the churning rate.
A Comparition on the Knowledge Management Level of Small Firms
Journal of Intelligence and Information Systems , volume 8, issue 2, 2002, Pages 37~49
The purpose of this research is to investigate the level of knowledge management in Korea small firms. The research scheme was experimented through a questionnaire survey answered by 150 firms. The research model was composed of five groups : 1) knowledge management and business strategic, 2) a culture and structure for knowledge management, 3) learning process and community 4) information technology to support knowledge management 5) a reward and performance measurement. The results of this research indicated that the level of knowledge management is different according to the characteristic of small firms. The result of the empirical analysis can be summarized as follows : First, the business culture for knowledge management is not performed pertinently. Second, the learning process for knowledge management and a reward and performance measurement is insufficient. Third, the characteristics of a fm should be considered for measuring the level of knowledge management.
Case-based Optimization Modeling
Journal of Intelligence and Information Systems , volume 8, issue 2, 2002, Pages 51~69
In the supply chain environment on the web, collaborative problem solving and case-based modeling has been getting more important, because it is difficult to cope with diverse problem requirements and inefficient to manage many models as well. Hence, the approach on case-based modeling is required. This paper provides a framework that generates a goal model based on multiple cases, modeling knowledge, and forward chaining and it also develops a search algorithm through sensitivity analysis to reduce the modeling effort.
Development of Integrated Planning System for Efficient Container Terminal Operation
Journal of Intelligence and Information Systems , volume 8, issue 2, 2002, Pages 71~89
In this paper, an integrated planning system is introduced for the efficient operation of container terminal. It consists of discharging and loading planning, yard planning, and berth scheduling subsystem. This interface of this system is considered for user's convenience, and the rule-based system is suggested and developed in order to make planning with automatic procedures, warning functions for errors.
Recommender System using Association Rule and Collaborative Filtering
Journal of Intelligence and Information Systems , volume 8, issue 2, 2002, Pages 91~103
A collaborative filtering which supports personalized services of users has been common use in existing web sites for increasing the satisfaction of users. A collaborative filtering is demanded that items are estimated more than specified number. Besides, it tends to ignore information of other users as recommending them on the basis of information of partial users who have similar inclination. However, there are valuable hidden information into other users' one. In this paper, we use Association Rule, which is common wide use in Data Mining, with collaborative filtering for the purpose of discovering those information. In addition, this paper proved that Association Rule applied to Recommender System has a effects to recommend users by the relation between groups. In other words, Association Rule based on the history of all users is derived from. and the efficiency of Recommender System is improved by using Association Rule with collaborative filtering.
A Study on the Recognition of an English Calling Card by using Contour Tracking Algorithm and Enhanced ART1
Journal of Intelligence and Information Systems , volume 8, issue 2, 2002, Pages 105~115
This paper proposed a recognition method of english calling card using both 4-directed contour tracking algorithm and enhanced ART1 algorithm. After we extract candidate character string region using horizontal smearing and 4-directed contour tracking method, we extract character string region through comparison of character region and non-character region using horizontal and vertical ratio and area in english calling card. In extracted character string region, we extract each character using horizontal smearing and contour tracking algorithm, and recognize each character by enhanced ART1 algorithm. The proposed ART1 algorithm is enhanced by dynamic control of similarity using fuzzy sum connective operator. The result indicate that the proposed method is superior in performance.
Feature Selection for Case-Based Reasoning using the Order of Selection and Elimination Effects of Individual Features
Journal of Intelligence and Information Systems , volume 8, issue 2, 2002, Pages 117~137
A CBR(Case-Based Reasoning) system solves the new problems by adapting the solutions that were used to solve the old problems. Past cases are retained in the case base, each in a specific form that is determined by features. Features are selected for the purpose of representing the case in the best way. Similar cases are retrieved by comparing the feature values and calculating the similarity scores. Therefore, the performance of CBR depends on the selected feature subsets. In this research, we measured the Selection Effect and the Elimination Effect of each feature. The Selection Effect is measured by performing the CBR with only one feature, and the Elimination Effect is measured by performing the CBR without only one feature. Based on these measurements, the feature subsets are selected. The resulting CBR showed better performance in terms of accuracy and efficiency than the CBR with all features.
A Personalized Recommendation Methodology based on Collaborative Filtering
Kim, Jae-Kyeong ; Suh, Ji-Hae ; Ahn, Do-Hyun ; Cho, Yoon-Ho ;
Journal of Intelligence and Information Systems , volume 8, issue 2, 2002, Pages 139~157
The rapid growth of e-commerce has made both companies and customers face a new situation. Whereas companies have become to be harder to survive due to more and more competitions, the opportunity for customers to choose among more and more products has increased. So, the recommender systems that recommend suitable products to the customer have an important position in E-commerce. This research introduces collaborative filtering based recommender system which helps customers find the products they would like to purchase by producing a list of top-N recommended products. The suggested methodology is based on decision tree, product taxonomy, and association rule mining. Decision tree is used to select target customers, who have high possibility of purchasing recommended products. We applied the recommender system to a Korean department store. The methodology is evaluated with the analysis of a real department store case and is compared with other methodologies.
Web Mining for successful e-Business based on Artificial Intelligence Techniques
Journal of Intelligence and Information Systems , volume 8, issue 2, 2002, Pages 159~175
Web mining is an emerging science of applying modem data mining technologies to the problem of extracting valid, comprehensible, and actionable information from large databases of web in e-Business environment and of using it to make crucial e-Business decisions. In this paper, we present the noble framework of data visualization system based on web mining for analyzing the characteristics of on-line customers in e-Business. We also propose the framework of forecasting system for providing the forecasting information of sales/purchase through the use of web mining based on artificial intelligence techniques such as back-propagation network, memory-based reasoning, and self-organizing map.
Design and development of the clustering algorithm considering weight in spatial data mining
Journal of Intelligence and Information Systems , volume 8, issue 2, 2002, Pages 177~187
Spatial data mining is a process to discover interesting relationships and characteristics those exist implicitly in a spatial database. Many spatial clustering algorithms have been developed. But, there are few approaches that focus simultaneously on clustering spatial data and assigning weight to non-spatial attributes of objects. In this paper, we propose a new spatial clustering algorithm, called DBSCAN-W, which is an extension of the existing density-based clustering algorithm DBSCAN. DBSCAN algorithm considers only the location of objects for clustering objects, whereas DBSCAN-W considers not only the location of each object but also its non-spatial attributes relevant to a given application. In DBSCAN-W, each datum has a region represented as a circle of various radius, where the radius means the degree of the importance of the object in the application. We showed that DBSCAN-W is effective in generating clusters reflecting the users requirements through experiments.
Comparison of Adaptive Operators in Genetic Algorithms
Yun, Young-Su ; Seo, Seoun-Lock ;
Journal of Intelligence and Information Systems , volume 8, issue 2, 2002, Pages 189~203
In this paper we compare the performances of adaptive operators in genetic algorithm. For the adaptive operators, the crossover and mutation operators of genetic algorithm are considered. One fuzzy logic controller is developed in this paper and two heuristics is presented from conventional works for constructing the operators. The fuzzy logic controller and two conventional heuristics adaptively regulate the rates of the operators during genetic search process. All the algorithms are tested and analyzed in numerical examples. Finally, the best algorithm is recommended.
Implementation of A Multiple-agent System for Conference Calling
Journal of Intelligence and Information Systems , volume 8, issue 2, 2002, Pages 205~227
Our study is focused on a multiple-agent system to provide efficient collaborative work by automating the conference calling process with the help of intelligent agents. Automating the meeting scheduling requires a careful consideration of the individual official schedule as well as the privacy and personal preferences. Therefore, the automation of conference calling needs the distributed processing task where a separate calendar management process is associated for increasing the reliability and inherent parallelism. This paper describes in detail the design and implementation issues of a multiple-agent system for conference calling that allows the convener and participants to minimize their efforts in creating a meeting. Our system is based on the client-sewer model. In the sewer side, a scheduling agent, a negotiating agent, a personal information managing agent, a group information managing agent, a session managing agent, and a coordinating agent are operating. In the client side, an interface agent, a media agent, and a collaborating agent are operating. Agents use a standardized knowledge manipulation language to communicate amongst themselves. Communicating through a standardized knowledge manipulation language allows the system to overcome heterogeneity which is one of the most important problems in communication among agents for distributed collaborative computing. The agents of our system propose the dates on which as many participants as possible are available to attend the conference using the forward chaining algorithm and the back propagation network algorithm.