Jin, D., Suh, Y., Lee, K., “Generation of Hypotheses on the Evolution of Agent-Based Business Using Inductive Learning,” Electronic Markets, vol. 13, no. 1, 13-20, 2003 (PDF)
Agent-based business in e-commerce can be defined as a business enabled and operated by software-agent technologies. The discrepancies between expectations on and reality of the business have raised research interests in its critical success factors. We suggest a framework for analysing the evolution of the agent-based business and analyse 16 representative agent-based business cases to derive explanatory variables seeming to have effect on the longevity of the agent-based business. The results of the case studies are used as an input to an inductive learning method to generate five theoretical hypotheses on its evolution. Finally, we provide strategic implications of the generated hypotheses about the evolution of the agent-based business.
Shin, K. Lee, K., Bankruptcy Prediction Modeling Using Multiple Neural Network Models, Lecture Notes in Artificial Intelligence 3214:668–674, September, 2004. – SCIE, ISSN:0302-9743
The primary goal of this paper is to get over the limitations of single neural network models through model integration so as to increase the accuracy of bankruptcy prediction. We take the closeness of the output value to either 0 or 1 as the models confidence in its prediction as to whether or not a company is going to bankrupt. In case where multiple models yield conflicting prediction results, our integrated model takes the output value of the highest confidence as the final output. The output of the confidence-based integration approach significantly increases the prediction performance. The results of composite prediction suggest that the proposed approach will offer improved performance in business classification problems by integrating case-specific knowledge with the confidence information and general knowledge with the multi-layer perceptrons generalization capability.
Shin, K., Lee, K., Kim, H., Support Vector Machines Approach to Pattern Detection in Bankruptcy Prediction and its Contingency, Lecture Notes in Computer Science 3316:1254-1259, November, 2004. – SCIE ISSN:0302-9743. pdf
This study investigates the effectiveness of support vector machines (SVM) approach in detecting the underlying data pattern for the corporate failure prediction tasks. Back-propagation neural network (BPN) has some limitations in that it needs a modeling art to find an appropriate structure and optimal solution and also large training set enough to search the weights of the network. SVM extracts the optimal solution with the small training set by capturing geometric characteristics of feature space without deriving weights of networks from the training data. In this study, we show the advantage of SVM approach over BPN to the problem of corporate bankruptcy prediction. SVM shows the highest level of accuracies and better generalization performance than BPN especially when the training set size is smaller.
Ko, K., Lee, K., Park, C., Rethinking Preferential Attachment Scheme in the dynamic network: Degree centrality or closeness centrality?, Connections 27(3):53-59, 2007. ISSN 0226-1776. pdf
Construction of realistic dynamic complex network has become increasingly important. One of widely known approaches, Barabasi and Albert’s “scale-free” network (BA network), has been generated under the assumption that new actors make ties with high degree actors. Unfortunately, degree, as a preferential attachment scheme, is limited to a local property of network structure, which social network theory has pointed out for a long time. In order to complement this shortcoming of degree preferential attachment, this paper not only introduces closeness preferential attachment, but also compares the relationships between the degree and closeness centrality in three different types of networks: random network, degree preferential attachment network, and closeness preferential attachment network. We show that a high degree is not a necessary condition for an actor to have high closeness. Degree preferential attachment network and sparse random network have relatively small correlation between degree and closeness centrality. Also, the simulation of closeness preferential attachment network suggests that individuals’ efforts to increase their own closeness will lead to inefficiency in the whole network.
Kim, H. Lee, K., Criteria of Good Project Network Generator and its Fulfillment using a Dynamic CBR Approach, Lecture Notes in Computer Science 3155:630-644, September, 2004. – SCIE, ISSN:0302-9743. pdf
Most project-based industries such as construction, shipbuilding, and software development etc. should generate and manage project network for successful project planning. We suggest a set of criteria of good project network generator such as network generation efficiency, quality of network, and economics of system development. For the efficiency of the planning, the first criterion, we decided to take a CBR approach. However, using only previous cases is insufficient to generate a proper network for a new project. By embedding rules and constraints in the case-based system, we could improve the quality of the project network: the second criterion. The integration of CBR approach and the knowledge-based approach makes feasible the development of the project network generator and improves the quality of the network by mutual enhancement through crosschecking the knowledge and cases in the development and maintenance stages. For some complex project network planning, a single-case assumed project network generation methodology is refined into Dynamic Leveled Multiple Case approach. The methodology contributes again the efficiency and effectiveness of project network generation and reduces the efforts of the system development.
Lee, J. K., Lee, K. J., Hong, J. S., Kim, W. J., Kim, E. Y., Choi, S. Y., Kim, H. D., Yang, O. R., Choi, H. R., “DAS: Intelligent Scheduling Systems for Shipbuilding”, AI Magazine, vol. 16, no. 2, pp. 78-94, Winter, 1995.pdf
Daewoo Shipbuilding Company, one of the largest shipbuilders in the world, has experienced a great deal of trouble with the planning and scheduling of its production process. To solve the problems, from 1991 to 1993, Korea Advanced Institute of Science and Technology (KAIST) and Daewoo jointly conducted the Daewoo Shipbuilding Scheduling (das) Project. To integrate the scheduling expert systems for shipbuilding, we used a hierarchical scheduling architecture. To automate the dynamic spatial layout of objects in various areas of the shipyard, we developed spatial scheduling expert systems. For reliable estimation of person-hour requirements, we implemented the neural network–based person-hour estimator. In addition, we developed the paneledblock assembly shop scheduler and the longrange production planner. For this large-scale project, we devised a phased development strategy consisting of three phases: (1) vision revelation, (2) data-dependent realization, and (3) prospective enhancement. The DAS systems were successfully launched in January 1994 and are actively being used as indispensable systems in the shipyard, resulting in significant improvement in productivity and visible and positive effects in many areas.
Lee, K. J., J. K. Lee, S. Y. Choi, “A Spatial Scheduling System and its Application to Shipbuilding: DAS-CURVE”, Expert Systems with Applications, vol. 10, no.3/4 , pp. 311-324, 1996.pdf
Spatial scheduling considers not only traditional scheduling constraints like resource capacity and due dates, but also dynamic spatial layout of the objects. Automation of spatial scheduling is particularly important when the spatial resources are critical bottleneck resources, as is the case in the shipbuilding industry. To develop a spatial scheduling expert system for shipbuilding, a methodology for spatial layout of polygonal objects within rectangular plates is first developed. This study is then extended to the methodology for spatial scheduling, including the time dimension. The methodology is applied to the scheduling of Daewoo shipbuilding to build a system DAS-CURVE. DAS-CURVE is successfully operational and its experimental performance is remarkable.
Lee, J. K., Lee, K. J., Park, H. K., Hong, J. S., Lee, J. S., “Developing Scheduling Systems for Daewoo Shipbuilding: DAS Project”, European Journal of Operational Research, vol. 97, no.2, pp.380-395, 1997.pdf
Daewoo Shipbuilding Company, one of the largest shipbuilders in the world, had difficulties with planning and scheduling its production process. To solve the problems, Korea Advanced Institute of Science and Technology (KAIST) and Daewoo have been jointly performing the DAS (DAewoo Shipbuilding Scheduling) Project for three years from 1991 to 1993. To develop the integrated scheduling systems, several technological breakthroughs were necessary such as hierarchical architecture between systems, constraint directed graph search, spatial scheduling, dynamic assembly line scheduling, and neural network based man-hours estimation. Besides these technological research issues, we adopted the phased development strategy, which consists of three phases of vision revelation, data dependent realization, and prospective enhancement. The DAS systems were successfully launched in January 1994 and are being actively used as indispensable systems in the shipyard resulting in a significant improvement in productivity and reengineering of the scheduling process.
Scheduling, Manufacturing Industries, Artificial Intelligence, Shipbuilding.
Lee, K. J., Kim, H. W., Lee, J. K. Kim, T. H., “FASTrak-APT: Case and Constraint-Based Construction Project Planning System”, AI Magazine, vol.19, no.1, pp.13-24, Spring, 1998.pdf
To effectively generate a fast and consistent apartment construction project network, Hyundai Engineering and Construction and Korea Advanced Institute of Science and Technology developed a case- and constraint-based project-planning expert system for an apartment domain. The system, FASTRAK- APT, is inspired by the use of previous cases by a human expert project planner for planning a new project and the modification of these cases by the project planner using his/her knowledge of domain constraints. This large-scale, case-based, and mixed-initiative planning system, integrated with intensive constraint-based adaptation, utilizes semantic-level metaconstraints and human decisions for compensating incomplete cases imbedding specific planning knowledge. The case- and constraint-based architecture inherently supports cross-checking cases with constraints during system development and maintenance. This system has drastically reduced the time and effort required for initial project planning, improved the quality and completeness of the generated plans, and is expected to give the company the competitive advantage in contract bids for new contracts.
Lee, K. J., “Sufficient Search Space in Spatial Expert Systems”, Expert Systems with Applications, vol. 19, no. 1, pp.1-8, July, 2000.pdf
This paper seeks the sufficient search space for the expert systems locating rectangular and arbitrary-shaped objects placed without rotation within a two-dimensional rectangular space. We found that for the layout of rectangular objects, the convex vertex set of feasible allocation space is a sufficient space to determine a feasible layout. We also found that for the layout of arbitrary-shaped objects, the boundary point set of the feasible allocation space is a sufficient space to determine a feasible layout. These two theorems are proved by developing two respective parallel translation algorithms. These theorems show that the search space can be significantly reduced in finding a feasible layout. Since these theorems were discovered while we were developing a spatial scheduling expert system, we have empirically tested the performance of the reduced search space with real world examples. According to the empirical test for the convex polygonal objects, the vertex set of feasible allocation space is satisfactory enough as a search space although the vertex set is not a sufficient space.