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Journal of Intelligence and Information Systems,
Vol. 16, No. 2, June 2010
Product Value Evaluation Models based on Itemset Association Chain
Yong-Sik Chang
Vol. 16, No. 2, Page: 1 ~ 17
Abstract
Association rules among product items by association analysis suggest sales effect among products. These are useful for marketing strategies such as cross-selling and product display etc. However, if we evaluate more practical product values reflecting cross-selling effects, they will be also more useful for the decisions of companies such as product item selection for product assortment and profit maximization etc. This study proposes product value evaluation models with the concept of effective value based on single-item association chain and itemset association chain. In addition to that, we performed experiments with transaction data related to clothing of an online shopping mall in Korea to show the performances of our models. In result, we confirmed that some items increased in effective values compared with their pure values while the others decreased in effective values.
A Study on Developing a VKOSPI Forecasting Model via GARCH Class Models for Intelligent Volatility Trading Systems
Sun-Woong Kim
Vol. 16, No. 2, Page: 19 ~ 32
Keywords : VKOSPI, GARCH
Abstract
Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.
Facilitating Web Service Taxonomy Generation : An Artificial Neural Network based Framework, A Prototype Systems, and Evaluation
You-Sub Hwang
Vol. 16, No. 2, Page: 33 ~ 54
Abstract
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 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 public Web service repositories have been proposed, but the Web service taxonomy generation has not been satisfactorily addressed. Unfortunately, most existing Web service taxonomies are either too rudimentary to be useful or too hard to be maintained. In this paper, we propose a Web service taxonomy generation framework that combines an artificial neural network based clustering techniques with descriptive label generating 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. 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 repositories. We report on some preliminary results demonstrating the efficacy of the proposed approach.
A Combat Effectiveness Evaluation Algorithm Considering Technical and Human Factors in C4I System
Whan-Sik Jung, Gun-Woo Park, Jae-Yeong Lee, and Sang-Hoon Lee
Vol. 16, No. 2, Page: 55 ~ 72
Keywords : Combat Effectiveness, Technical Factors, Human Factors, C2 Theory, Newton's Second Law, E-TechMan algorithm
Abstract
Recently, the battlefield environment has changed from platform-centric warfare(PCW) which focuses on maneuvering forces into network-centric warfare(NCW) which is based on the connectivity of each asset through the warfare information system as information technology increases. In particular, C4I(Command, Control, Communication, Computer and Intelligence) system can be an important factor in achieving NCW. It is generally used to provide direction across distributed forces and status feedback from thoseforces. It can provide the important information, more quickly and in the correct format to the friendly units. And it can achieve the information superiority through SA(Situational Awareness). Most of the advanced countries have been developed and already applied these systems in military operations. Therefore, ROK forces also have been developing C4I systems such as KJCCS(Korea Joint Command Control System). And, ours are increasing the budgets in the establishment of warfare information systems. However, it is difficult to evaluate the C4I effectiveness properly by deficiency of methods. We need to develop a new combat effectiveness evaluation method that is suitable for NCW. Existing evaluation methods lay disproportionate emphasis on technical factors with leaving something to be desired in human factors. Therefore, it is necessary to consider technical and human factors to evaluate combat effectiveness. In this study, we proposed a new Combat Effectiveness evaluation algorithm called E-TechMan(A Combat Effectiveness Evaluation Algorithm Considering Technical and Human Factors in C4I System). This algorithm uses the rule of Newton's second law. Five factors considered in combat effectiveness evaluation are network power(M), movement velocity(v), information accuracy(I), command and control time(T) and collaboration level(C). Previous researches did not consider the value of the node and arc in evaluating the network power after the C4I system has been established. In addition, collaboration level which could be a major factor in combat effectiveness was not considered. E-TechMan algorithm is applied to JFOS-K(Joint Fire Operating System-Korea) system that can connect KJCCS of Korea armed forces with JADOCS(Joint Automated Deep Operations Coordination System) of U.S. armed forces and achieve sensor to shooter system in real time in JCS(Joint Chiefs of Staff) level. We compared the result of evaluation of Combat Effectiveness by E-TechMan with those by other algorithms(e.g., C2 Theory, Newton's second Law). We can evaluate combat effectiveness more effectively and substantially by E-TechMan algorithm. This study is meaningful because we improved the description level of reality in calculation of combat effectiveness in C4I system. Part 2 will describe the changes of war paradigm and the previous combat effectiveness evaluation methods such as C2 theory while Part 3 will explain E-TechMan algorithm specifically. Part 4 will present the application to JFOS-K and analyze the result with other algorithms. Part 5 is the conclusions provided in the final part.
A Study on Design of Agent based Nursing Records System in Attending System
Kyoung-Hwan Kim
Vol. 16, No. 2, Page: 73 ~ 94
Keywords : Nursing Records, Attending System, Agent Based System
Abstract
The attending system is a medical system that allows doctors in clinics to use the extra equipment in hospitals-beds, laboratory, operating room, etc-for their patient's care under a contract between the doctors and hospitals. Therefore, the system is very beneficial in terms of the efficiency of the usage of medical resources. However, it is necessary to develop a strong support system to strengthen its weaknesses and supplement its merits. If doctors use hospital beds under the attending system of hospitals, they would be able to check a patient's condition often and provide them with nursing care services. However, the current attending system lacks delivery and assistance support. Thus, for the successful performance of the attending system, a networking system should be developed to facilitate communication between the doctors and nurses. In particular, the nursing records in the attending system could help doctors monitor the patient's condition and provision of nursing care services. A nursing record is the formal documentation associated with nursing care. It is merely a data repository that helps nurses to track their activities; nursing records thus represent a resource of primary information that can be reused. In order to maximize their usefulness, nursing records have been introduced as part of computerized patient records. However, nursing records are internal data that are not disclosed by hospitals. Moreover, the lack of standardization of the record list makes it difficult to share nursing records. Under the attending system, nurses would want to minimize the amount of effort they have to put in for the maintenance of additional records. Hence, they would try to maintain the current level of nursing records in the form of record lists and record attributes, while doctors would require more detailed and real-time information about their patients in order to monitor their condition. Therefore, this study developed a system for assisting in the maintenance and sharing of the nursing records under the attending system. In contrast to previous research on the functionality of computer-based nursing records, we have emphasized the practical usefulness of nursing records from the viewpoint of the actual implementation of the attending system. We suggested that nurses could design a nursing record dictionary for their convenience, and that doctors and nurses could confirm the definitions that they looked up in the dictionary through negotiations with intelligent agents. Such an agent-based system could facilitate networking among medical institutes. Multi-agent systems are a widely accepted paradigm for the distribution and sharing of computation workloads in the scientific community. Agent-based systems have been developed with differences in functional cooperation, coordination, and negotiation. To increase such communication, a framework for a multi-agent based system is proposed in this study. The agent-based approach is useful for developing a system that promotes trade-offs between transactions involving multiple attributes. A brief summary of our contributions follows. First, we propose an efficient and accurate utility representation and acquisition mechanism based on a preference scale while minimizing user interactions with the agent. Trade-offs between various transaction attributes can also be easily computed. Second, by providing a multi-attribute negotiation framework based on the attribute utility evaluation mechanism, we allow both the doctors in charge and nurses to negotiate over various transaction attributes in the nursing record lists that are defined by the latter. Third, we have designed the architecture of the nursing record management server and a system of agents that provides support to the doctors and nurses with regard to the framework and mechanisms proposed above. A formal protocol has also been developed to create and control the communication required for negotiations. We verified the realization of the system by developing a web-based prototype. The system was implemented using ASP and IIS5.1.
Dynamic Hand Gesture Recognition Using CNN Model and FMM Neural Networks
Ho-Joon Kim
Vol. 16, No. 2, Page: 95 ~ 108
Keywords : Hand Gesture Recognition, Neural Network, Feature Extraction
Abstract
In this paper, we present a hybrid neural network model for dynamic hand gesture recognition. The model consists of two modules, feature extraction module and pattern classification module. We first propose a modified CNN(convolutional Neural Network) a pattern recognition model for the feature extraction module. Then we introduce a weighted fuzzy min-max(WFMM) neural network for the pattern classification module. The data representation proposed in this research is a spatiotemporal template which is based on the motion information of the target object. To minimize the influence caused by the spatial and temporal variation of the feature points, we extend the receptive field of the CNN model to a three-dimensional structure. We discuss the learning capability of the WFMM neural networks in which the weight concept is added to represent the frequency factor in training pattern set. The model can overcome the performance degradation which may be caused by the hyperbox contraction process of conventional FMM neural networks. From the experimental results of human action recognition and dynamic hand gesture recognition for remote-control electric home appliances, the validity of the proposed models is discussed.
The Study on the Network Targeting Using the Non-financial Value of Customer
Jin Kim, Yoon-Jo Oh, Joo-Seok Park, Kyung-Hee Kim, and Jung-Hyun Lee
Vol. 16, No. 2, Page: 109 ~ 128
Keywords : Network Marketing, Social Network, Social Network Analysis, Customer Targeting, Recommendation, Neighbor, Degree Centrality, Closeness Centrality Data-based Marketing, Network Targeting
Abstract
The purpose of our research is to figure out the 'non-financial value' of consumers applying networks amongst consumer groups, the data-based marketing strategy to the analysis and delve into the ways for enhancing effectives in marketing activities by adapting the value to the marketing. To verify the authenticity of the points, we did the empirical test on the consumer group using 'the Essence Cosmetics Products' of high involvement that is deeply affected by consumer perceptions and the word-of-mouth activities. 1) The empirical analysis reveals the following features. First, the segmented market for 'Essence Consumer' is composed of several independent networks, each network shows to have the consumers that is high degree centrality and closeness centrality. Second, the result proves the authenticity of the non-financial value for boosting corporate profits by the high degree centrality and closeness centrality consumer's word-of-mouth activities. Lastly, we verify that there lies a difference in the network structure of 'Essence Cosmetics Market'per each product origin(domestic, foreign) and demographic characteristics. It does, therefore, indicate the need to consider the features applying mutually complementary for the network targeting.
An Efficient Heuristic for Storage Location Assignment and Reallocation for Products of Different Brands at Internet Shopping Malls for Clothing
Yong-Uk Song, and Byung-Hyuk Ahn
Vol. 16, No. 2, Page: 129 ~ 141
Keywords : Internet Shopping Mall, Order Picking, Reallocation, Warehouse
Abstract
An Internet shopping mall for clothing operates a warehouse for packing and shipping products to fulfill its orders. All the products in the warehouse are put into the boxes of same brands and the boxes are stored in a row on shelves equiped in the warehouse. To make picking and managing easy, boxes of the same brands are located side by side on the shelves. When new products arrive to the warehouse for storage, the products of a brand are put into boxes and those boxes are located adjacent to the boxes of the same brand. If there is not enough space for the new coming boxes, however, some boxes of other brands should be moved away and then the new coming boxes are located adjacent in the resultant vacant spaces. We want to minimize the movement of the existing boxes of other brands to another places on the shelves during the warehousing of new coming boxes, while all the boxes of the same brand are kept side by side on the shelves. Firstly, we define the adjacency of boxes by looking the shelves as an one dimensional series of spaces to store boxes, i.e. cells, tagging the series of cells by a series of numbers starting from one, and considering any two boxes stored in the cells to be adjacent to each other if their cell numbers are continuous from one number to the other number. After that, we tried to formulate the problem into an integer programming model to obtain an optimal solution. An integer programming formulation and Branch-and-Bound technique for this problem may not be tractable because it would take too long time to solve the problem considering the number of the cells or boxes in the warehouse and the computing power of the Internet shopping mall. As an alternative approach, we designed a fast heuristic method for this reallocation problem by focusing on just the unused spaces-empty cells-on the shelves, which results in an assignment problem model. In this approach, the new coming boxes are assigned to each empty cells and then those boxes are reorganized so that the boxes of a brand are adjacent to each other. The objective of this new approach is to minimize the movement of the boxes during the reorganization process while keeping the boxes of a brand adjacent to each other. The approach, however, does not ensure the optimality of the solution in terms of the original problem, that is, the problem to minimize the movement of existing boxes while keeping boxes of the same brands adjacent to each other. Even though this heuristic method may produce a suboptimal solution, we could obtain a satisfactory solution within a satisfactory time, which are acceptable by real world experts. In order to justify the quality of the solution by the heuristic approach, we generate 100 problems randomly, in which the number of cells spans from 2,000 to 4,000, solve the problems by both of our heuristic approach and the original integer programming approach using a commercial optimization software package, and then compare the heuristic solutions with their corresponding optimal solutions in terms of solution time and the number of movement of boxes. We also implement our heuristic approach into a storage location assignment system for the Internet shopping mall.
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