• The KIPS Transactions:PartB
• /
• v.15B no.1
• /
• pp.61-68
• /
• 2008

This paper presents a spam filter system using co-training with spamminess features and URL features based on the maximum entropy model. Spamminess features are the emphasizing patterns or abnormal patterns in spam messages used by spammers to express their intention and to avoid being filtered by the spam filter system. Since spammers use URLs to give the details and make a change to the URL format not to be filtered by the black list, normal and abnormal URLs can be key features to detect the spam messages. Co-training with spamminess features and URL features uses two different features which are independent each other in training. The filter system can learn information from them independently. Experiment results on TREC spam test collection shows that the proposed approach achieves 9.1% improvement and 6.9% improvement in accuracy compared to the base system and bogo filter system, respectively. The result analysis shows that the proposed spamminess features and URL features are helpful. And an experiment result of the co-training shows that two feature sets are useful since the number of training documents are reduced while the accuracy is closed to the batch learning.

• Journal of Internet Computing and Services
• /
• v.8 no.6
• /
• pp.75-85
• /
• 2007

One of important factors for improving the learning achievement of students in computer programming education is to provide plenty of opportunities of problem-solving experiences through variety forms of assignments, However, for the most cases, evaluation of programming assignments is performed manually by instructors and automated tools for the accurate evaluation are not equipped at the present time. Under this restricted environment instructors need much work and time to grade assignments so that instructors could not deliver sufficient programming assignments to students, In order to overcome this problem. au automated programming assignment evaluation system is needed that would enable instructors to evaluate assignments easily in an effective and consistent way and also to detect any plagiarism activities among students in program source codes readily, Accordingly, in this paper we design and implement a Web-based programming assignment grading system that allows instructors to evaluate program performance automatically as well as to evaluate program styles and piagiarism easily with appropriate feedback.

• Journal of KIISE:Software and Applications
• /
• v.31 no.7
• /
• pp.849-858
• /
• 2004

Most of supervised teaming algorithms could be applied after that continuous variables are transformed to categorical ones at the preprocessing stage in order to avoid the difficulty of processing continuous variables. This preprocessing stage is called global discretization, uses the class distribution list called bins. But, when data are large and the range of the variable to be discretized is very large, many sorting and merging should be performed to produce a single bin because most of global discretization methods need a single bin. Also, if new data are added, they have to perform discretization from scratch to construct categories influenced by the data because the existing methods perform discretization in batch mode. This paper proposes a method that extracts sample points and performs discretization from these sample points in order to solve these problems. Because the approach in this paper does not require merging for producing a single bin, it is efficient when large data are needed to be discretized. In this study, an experiment using real and synthetic datasets was made to compare the proposed method with an existing one.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.5
• /
• pp.457-463
• /
• 2015

This paper presents the need for the concept of collective intelligence based system for the timely learning and incorrect notes show the utilization and satisfaction. The old wrong answer note system is characterized by the provision of uniform right answer explanations for the questions whose answers were wrong by checking whether the evaluation items were answered right or wrong. The characteristic requires a lot of improvements in terms of wrong answer analysis and feedback since it cannot properly receive feedback on the items that a learner got right by luck in spite of poor understanding of them and on the errors in the selection process of wrong answers by individual learners. The SERO wrong answer note was designed to propose new ways to identify and capture such "score errors" and compensate for the practical weaknesses of learners. The Stability Emergency Risk Opportunity (SERO) wrong answer note is based on a method of categorizing and analyzing evaluation items answered by the examinee into four types (S, E, R and O type), and commentary correct as well as incorrect answers by presenting a variety of commentary notes using the collective intelligence of the study show that satisfaction is high.

• Journal of Elementary Mathematics Education in Korea
• /
• v.20 no.4
• /
• pp.695-715
• /
• 2016

This study is on the teaching method for the students who belong to the same school (one, the gifted class, passed gifted education of Science High school ), 1-1, face-to-face learning (two, good students in regular classroom) with a teacher, paired learning teams (4 people, gifted classes), and group lessons (20 people, gifted classes) and using the justification analysis framework tool(PIRSO) of Kim(2010) analyzes the justification element of the students in the group classes regular polygons paper was to explore ways to improve the justification of the folding maps activities. As a result, the width of the largest polygon difficulty level appropriate to the class for gifted elementary school classes but the individual learning style of the 1-1 face-to-face with a teacher or discussion with colleagues and cooperative approach is justified, rather than the material of the study of origami activities it turned out to be more effective in improving the level of justification. Unlike the individual learning activities, the exploration for class is the need to strain in parallel to the student is selected as needed, rather than serial manner was confirmed that it is necessary to clearly present problems even from the beginning. Development of teaching through the implications obtained from this method of reconstruction activities and proposed improvement measures for questioning.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2003.05a
• /
• pp.313-316
• /
• 2003

인터넷 기반 서비스업체들이 기하급수적으로 늘어나면서 업체들은 다른 업체들과는 차별화 시킬 수 있고, 사용자들에는 친근감을 제공하기 위해서 캐릭터 에이전트 연구를 진행 중에 있다. 그러나 현재 서비스되고 있는 캐릭터들은 사용자맞춤형이 아닌 단지 페이지기반으로 모든 사용자들에게 일괄적인 감정, 행동을 보여주고 있다. 이러한 방법은 항상, 누구에게나 같은 서비스를 해줌으로써 점차 사용자들의 신뢰성이 떨어질 수밖에 없다. 본 논문에서는 이러한 캐릭터 에이전트들의 신뢰성 증가를 위하여 사용자와 상호작용하면서 사용자의 성향을 파악하고 이를 학습하여 감정을 생성, 표현하는 Interactive, personalized, emotional 지능형 에이전트를 개발하고자 한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.10 no.1
• /
• pp.38-45
• /
• 2017

Attacking of computer and network is increasing as information processing technology heavily depends on computer and network. To prevent the attack of system and network, host and network based intrusion detection system has developed. But previous rule based system has a lot of difficulties. For this reason demand for developing a intrusion detection system which detects and cope with the attack of system and network resource in real time. In this paper we develop a real time intrusion detection system which is combination of APEX and LS-SVM classifier. Proposed system is for nonlinear data and guarantees convergence. While real time processing system has its advantages, such as memory efficiency and allowing a new training data, it also has its disadvantages of inaccuracy compared to batch way. Therefore proposed real time intrusion detection system shows similar performance in accuracy compared to batch way intrusion detection system, it can be deployed on a commercial scale.

• Journal of the Korean Society for Railway
• /
• v.19 no.3
• /
• pp.314-323
• /
• 2016

Overhead line voltage of DC railway traction substations has rising or falling characteristics depending on the acceleration and regenerative braking of the subway train loads. The suppression of this irregular fluctuation of the line voltage gives rise to improved energy efficiency of both the railway substation and the trains. This paper presents parameter estimation schemes using the RC circuit model for an overhead line voltage at a 1500V DC electric railway traction substation. A linear artificial neural network with a back-propagation learning algorithm was trained using the measurement data for an overhead line voltage and four feeder currents. The least square estimation method was configured to implement batch processing of these measurement data. These estimation results have been presented and performance analysis has been achieved through raw data simulation.

• Journal of Broadcast Engineering
• /
• v.27 no.6
• /
• pp.872-884
• /
• 2022

With the development of the IoT industry, different types of time series data are being generated in various industries, and it is evolving into research that reproduces and utilizes it through re-integration. In addition, due to data processing speed and issues of the utilization system in the actual industry, there is a growing tendency to compress the size of data when using time series data and integrate it. However, since the guidelines for integrating time series data are not clear and each characteristic such as data description time interval and time section is different, it is difficult to use it after batch integration. In this paper, two integration methods are proposed based on the integration criteria setting method and the problems that arise during integration of time series data. Based on this, integration framework of a heterogeneous time series data was constructed that is considered the characteristics of time series data, and it was confirmed that different heterogeneous time series data compressed can be used for integration and various machine learning.

• Journal of the Korean Applied Science and Technology
• /
• v.37 no.6
• /
• pp.1752-1763
• /
• 2020

The purpose of the study is to examine the relationship between teacher enthusiasm, support for teacher autonomy, support for relationship with peers, and grit for preliminary high school students. This will be able to provide useful information for effective instruction and search for various teaching-learning methods in the physical education field. It was selected based on convenience sampling and judgmental sampling, focusing on those who participate in physical education classes for middle school students. Of the 200 respondents to the questionnaire, the study was conducted through 182 copies, excluding 18 questionnaires that were judged to be unreliable or responded collectively. When looking at the effects of physical education teachers' passion on autonomy support and relationship support, the hypothesis was adopted as it was found to have a statistically significant effect. Relationship support appeared to have a statistically significant effect on grit, so the hypothesis was adopted. However, support for autonomy was rejected as it did not appear to have a statistically significant effect on grit.