• Journal of the Korean Society for information Management
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• v.14 no.2
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• pp.213-234
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• 1997

A stemming algorithm for the Korean language free-text retrieval system has been designed and implemented. The algorithm contains three major parts and it operates iteratively ; firstly, stop-words are removed with a use of a stop-word list ; secondly, a basic removing procedure proceeds with a rule table 1, which contains the suffixes, the postpositional particles, and the optionally adopted symbols specifying an each stemming action ; thirdly, an extended stemming and rewriting procedures continue with a rule table 2, which are composed of th suffixes and the optionally combined symbols representing various actions depending upon the context-sensitive rules. A test was carried out to obtain an indication of how successful the algorithm was and to identify any minor changes in the algorithm for an enhanced one. As a result of it, 21.4 % compression is achieved and an error rate is 15.9%.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.237-245
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• 2001

Automated essay grading has been proposed for over thirty years. Only recently have practical implementations been constructed and tested. This paper investigated the role of the nearest-neighbour algorithm within the information retrieval as a way of grading the essay automatically called Automated Essay Grading System. It intended to offer teachers an individualized assistance in grading the student\`s essay. The system involved several processes, which are the indexing, the structuring of the model answer and the grade processing. The indexing process comprised the document indexing and query processing which are mainly used for representing the documents and the query. Structuring the model answer is actually preparing the marking scheme and the grade processing is the process of assessing the essay. To test the effectiveness of the developed algorithms, the algorithms are tested against the History text in Malay. The result showed that th information retrieval and the nearest-neighbour algorithm are practical combination that offer acceptable performance for grading the essay.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.3
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• pp.170-177
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• 2010

Poker is a game of imperfect information where competing players must deal with multiple risk factors stemming from unknown information while making the best decision to win, and this makes it an interesting test-bed for artificial intelligence research. This paper introduces a new learning AI algorithm with embedded opponent modeling that can be used for these types of situations and we use this AI and apply it to a poker program. The new AI will be based on several graphs with each of its nodes representing inputs, and the algorithm will learn the optimal decision to make by updating the weight of the edges connecting these nodes and returning a probability for each action the graphs represent.

• Journal of the Korea Society for Simulation
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• v.12 no.2
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• pp.1-11
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• 2003

In this paper, we focus an optimal policy focus optimal class of (s, S) inventory control systems. To this end, we use the perturbation analysis and apply a stochastic optimization algorithm to minimize the average cost over a period. We obtain the gradients of objective function with respect to ordering amount S and reorder point s via a combined perturbation method. This method uses the infinitesimal perturbation analysis and the smoothed perturbation analysis alternatively according to occurrences of ordering event changes. Our simulation results indicate that the optimal estimates of s and S obtained from a stochastic optimization algorithm are quite accurate. We consider that this may be due to the estimated gradients of little noise from the regenerative system simulation, and their effect on search procedure when we apply the stochastic optimization algorithm. The directions for future study stemming from this research pertain to extension to the more general inventory system with regard to demand distribution, backlogging policy, lead time, and review period. Another directions involves the efficiency of stochastic optimization algorithm related to searching procedure for an improving point of (s, S).

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.89-97
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• 2019

This study proposes a method for investigating current patents related to information communication technology and smart mobility to provide insights into future technology trends. The method is based on text mining clustering analysis. The method consists of two stages, which are data preparation and clustering analysis, respectively. In the first stage, tokenizing, filtering, stemming, and feature selection are implemented to transform the data into a usable format (structured data) and to extract useful information for the next stage. In the second stage, the structured data is partitioned into groups. The K-medoids algorithm is selected over the K-means algorithm for this analysis owing to its advantages in dealing with noise and outliers. The results of the analysis indicate that most current patents focus mainly on smart connectivity and smart guide systems, which play a major role in the development of smart mobility.

• Journal of the Korea Society for Simulation
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• v.12 no.3
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• pp.31-40
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• 2003

This paper studies an optimal policy for a certain class of (s, S) inventory control systems, where the demands are characterized by the renewal arrival process. To minimize the average cost over a simulation period, we apply a stochastic optimization algorithm which uses the gradients of parameters, s and S. We obtain the gradients of objective function with respect to ordering amount S and reorder point s via a combined perturbation method. This method uses the infinitesimal perturbation analysis and the smoothed perturbation analysis alternatively according to occurrences of ordering event changes. The optimal estimates of s and S from our simulation results are quite accurate. We consider that this may be due to the estimated gradients of little noise from the regenerative system simulation, and their effect on search procedure when we apply the stochastic optimization algorithm. The directions for future study stemming from this research pertain to extension to the more general inventory system with regard to demand distribution, backlogging policy, lead time, and inter-arrival times of demands. Another direction involves the efficiency of stochastic optimization algorithm related to searching procedure for an improving point of (s, S).

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.27-37
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• 2020

In this paper, we propose the methodology based on data-driven approach using Natural Language Processing and Machine Learning for classifying requirements into functional requirements and non-functional requirements. Through the analysis of the results of the requirements classification, we have learned that the trained models derived from requirements classification with data-preprocessing and classification algorithm based on the characteristics and information of existing requirements that used term weights based on TF and IDF outperformed the results that used stemming and stop words to classify the requirements into functional and non-functional requirements. This observation also shows that the term weight calculated without removal of the stemming and stop words influenced the results positively. Furthermore, we investigate an optimized method for the study of classifying software requirements into functional and non-functional requirements.

• Journal of Korea Multimedia Society
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• v.4 no.5
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• pp.390-395
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• 2001

In this paper, we propose a fast warping prediction using bit-pattern for motion estimation. Because of the spatial dependency between motion vectors of neighboring node points carrying motion information, the optimization of motion search requires an iterative search. The computational load stemming from the iterative search is one of the major obstacles for practical usage of warping prediction. The motion estimation in the proposed algorithm measures whether the motion content of the area is or not, using bit-pattern. Warping prediction using the motion content of the area make the procedure of motion estimation efficient by eliminating an unnecessary searching. Experimental results show that the proposed algorithm can reduce more 75% iterative search while maintaining performances as close as the conventional warping prediction.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.7
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• pp.725-732
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• 2013

This paper presents a torque distribution algorithm for improving the stability and mobility of a wall-climbing robot platform. During ascent, the pitch moment caused by the payload or external disturbances separates the robot's triangular tracks from the wall, significantly deteriorating its stability. Moreover, the reaction forces stemming from the increase in the pulling force may degrade the robot's mobility. Thus, it is very important to minimize the reaction forces acting on the triangular tracks, as well as the fluctuations in the pulling force, during the climb. Through dynamic modeling of the proposed robot platform, we demonstrated the dependence of the robot's stability and mobility on the torque distribution of the triangular tracks. Extensive simulations using different climbing speeds were used to significantly improve the stability and mobility of the proposed robot platform.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.39-47
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• 2018

The Dial Algorithm, based on single link based calculation, is unable to reflect cyclic paths arising in actual urban transportation networks. At the same time, redefining the paths more efficiently can, by strict standards, lead to irrational results stemming from reduction in the size of the network to be analyzed. To solve these two problems of the Dial algorithm, the research herein proposes a vine network method applied to a link based Dial Algorithm, in which the original three step alogrithm is modified into a vine network-based three step process. Also, an analysis of two case study networks show feasible replication of the predicted cyclic path, unrealistic flow, and unsteady transit, as well as alleviation of the problem of irrational path allocation.