이경전, 홍성우, NFC 기반 세렌디피티 시스템 설계, 지능정보연구, 17(4), 2011.(PDF) in Korean
The world of ubiquitous computing is one in which we will be surrounded by an ever-richer set of networked devices and services. Especially, mobile phone now becomes one of the key issues in ubiquitous computing environments. Mobile phones have been infecting our normal lives more thoroughly, and are the fastest technology in human history that has been adapted to people. In Korea, the number of mobile phones registered to the telecom company, is more than the population of the country. Last year, the numbers of mobile phone sold are many times more than the number of personal computer sold. The new advanced technology of mobile phone is now becoming the most concern on every field of technologies. The mix of wireless communication technology (wifi) and mobile phone (smart phone) has made a new world of ubiquitous computing and people can always access to the network anywhere, in high speed, and easily. In such a world, people cannot expect to have available to us specific applications that allow them to accomplish every conceivable combination of information that they might wish. They are willing to have information they want at easy way, and fast way, compared to the world we had before, where we had to have a desktop, cable connection, limited application, and limited speed to achieve what they want. Instead, now people can believe that many of their interactions will be through highly generic tools that allow end-user discovery, configuration, interconnection, and control of the devices around them. Serendipity is an application of the architecture that will help people to solve a concern of achieving their information. The word ‘serendipity’, introduced to scientific fields in eighteenth century, is the meaning of making new discoveries by accidents and sagacity. By combining to the field of ubiquitous computing and smart phone, it will change the way of achieving the information. Serendipity may enable professional practitioners to function more effectively in the unpredictable, dynamic environment that informs the reality of information seeking. This paper designs the Serendipity Service based on NFC (Near Field Communication) technology. When users of NFC smart phone get information and services by touching the NFC tags, serendipity service will be core services which will give an unexpected but valuable finding. This paper proposes the architecture, scenario and the interface of serendipity service using tag touch data, serendipity cases, serendipity rule base and user profile.
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.
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.
Kim, H., Lee, K., Kim, J., A Peer-to-Peer CF-Recommendation for Ubiquitous Environment, Lecture Notes in Computer Science 4088: 678-683, 2006.pdf
In ubiquitous environment where all entities can freely connect and collaborate with each other from anywhere, the amount of accessible information is overwhelming and desired information often remains unfound. So there is a growing need to provide the personalized recommendation services for the customers in ubiquitous space. This paper suggests a UREC_P2P (U-Recommendation by peer-to-peer), a recommendation procedure in ubiquitous environment adopting P2P technologies combined with collaborative filtering algorithm. UREC_P2P is implemented and comparatively evaluated with a CFbased recommender system in client-server environment. The evaluation result shows that UREC_P2P has a good potential to be a preeminent and realistic solution to the recommendation problems encountered in ubiquitous environment.