• Journal of Internet Computing and Services
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• v.7 no.6
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• pp.1-10
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• 2006

A software development using components reuse is an useful method to reduce the software development cost. But a retrieval method by the keyword and category classifications is difficult to search an exact matching component due to components complexity in component reuse. Therefore, after different existing methods are examined and analyzed, an effective classification and retrieval method using XML specifications and the system architecture of components integrated management based on it are presented. Many discording elements of DTD which is component meta-expression exist in components retrieval. To compensate it, this retrieval method using estimations of precision and concision is effective one to catch considerable matching preference components. This method makes possible to retrieve suitable components having better priority due to searching similar matching components that are difficult in an existing keyword matching method.

• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.59-66
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• 2021

Recently, conceptual information model is changing fast, and these changes are coming about as a result of individual tendency, social cultural, new circumstances and societal shifts within big data environment. Despite the data is growing more and more, now is the time to commit ourselves to the development of renewable, invaluable information of social/live commerce. Because we have problems with various insoluble data, we propose about deep learning prediction model-based object classification in social commerce of big data environment. Accordingly, it is an increased need of social commerce platform capable of handling high volumes of multiple items by users. Consequently, responding to rapid changes in users is a very significant by deep learning. Namely, promptly meet the needs of the times, and a widespread growth in big data environment with the goal of realizing in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4191-4211
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• 2019

Software product lines (SPLs) are complex software systems by nature due to their common reference architecture and interdependencies. Therefore, any form of evolution can lead to a more complex situation than a single system. On the other hand, software product lines are developed keeping long-term perspectives in mind, which are expected to have a considerable lifespan and a long-term investment. SPL development organizations need to consider software evolution in a systematic way due to their complexity and size. Addressing new user requirements over time is one of the most crucial factors in the successful implementation SPL. Thus, the addition of new requirements or the rapid context change is common in SPL products. To cope with rapid change several researchers have discussed the evolution of software product lines. However, for the evolution of an SPL, the literature did not present a systematic process that would define activities in such a way that would lead to the rapid evolution of software. Our study aims to provide a requirements-driven process that speeds up the requirements engineering process using social network sites in order to achieve rapid software evolution. We used classification, topic modeling, and sentiment extraction to elicit user requirements. Lastly, we conducted a case study on the smartwatch domain to validate our proposed approach. Our results show that users' opinions can contain useful information which can be used by software SPL organizations to evolve their products. Furthermore, our investigation results demonstrate that machine learning algorithms have the capacity to identify relevant information automatically.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.301-311
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• 2023

In university liberal arts education, learners' achievement goals are an important research topic, and this also applies to liberal arts software education. In this paper, we analyzed changes in learning motivation of learners taking liberal arts software courses according to course classification using a 3 × 2 achievement goal model. The analysis was conducted on a discussion-oriented class taken together by learners receiving credits for different purposes, such as required and elective. As a result, it was confirmed that learners begin the semester with similar achievement goals. However, the avoidance goals of learners taking elective courses decreased, showing a significant difference at the end of the semester. It was a different result from the existing liberal arts software education studies that pointed to mandatory enrollment as the cause of lack of motivation to learn. In addition, it was confirmed that learners who take elective courses relatively focus on achievement rather than competition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.641-642
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• 2011

This paper presents method of constructing the embedded systems based on hardware-software codesign which is the important fields of $21^{st}$ information technology. First, we describe the classification and necessity of embedded systems, and we discuss the consideration and classification for constructing the embedded systems. Also, we discuss the embedded systems modeling. The proposed embedded systems based on hardware-software co-design is important gradually, we expect that it involve the many IT fields in the future.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.535-536
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• 2016

사람이 수많은 지원자의 이력서들을 모두 꼼꼼히 읽는 데에는 엄청난 시간과 노동이 필요하다. 만약 컴퓨터가 이력서를 알맞은 직군으로 분류해 줄 수 있다면 이러한 어려움을 해소할 수 있다. 이를 위해 본 논문에서는 알맞은 직군으로 분류하기 위한 이력서를 학습할 때에 feature를 어떤 방법으로 선택할 수 있는지 그리고 feature의 개수는 몇 개가 적절한지에 대해 알아본다.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.1-6
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• 2013

For predicting defect-prone module in software, SVM classifier showed good performance in a previous research. But there are disadvantages that SVM parameter should be chosen differently for every kernel, and algorithm should be performed iteratively for predict results of changed parameter. Therefore, we find these parameters using Genetic Algorithm and compare with result of classification by Backpropagation Algorithm. As a result, the performance of GA-SVM model is better.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.147-148
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• 2019

네트워크 응용 서비스들은 점점 더 복잡해지고 있으며, 네트워크 통신 기술의 발전과 함께 네트워크의 특성, 네트워크 관리 및 혼잡 제어에 대한 높은 요구 사항을 제시하므로 네트워크 트래픽 분류가 점점 더 중요해지고 있다. 트래픽 분류는 다양한 특성에 따라 네트워크 트래픽을 여러 클래스로 분류하여 처리하는 작업이다. 본 논문에서는 현재 네트워크 분야에서 적용된 여러 트래픽 분류 기법을 조사한다. 이를 통해 SDN(Software Defined Networking) 환경에서 효율적인 트래픽 분류가 가능한 기법 선택을 위해 비교하며 향후 연구를 위해 트래픽 분류 기법들을 소개한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.267-270
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• 2019

Through this research, the rating data of shops were analyzed. The model was designed for discrete multiple classification as to the corresponding data, and the following experiments were initiated to observe the learned machine. By comparing each benchmarks in the experiments, which contains different setting variables for the machine model, the hit ratio was measured which indicates how much it is matched with the expected label. By analyzing those results from each benchmarks, the model was redesigned one time during the research and the effects of each setting variables on this machine were clarified. Furthermore, the research result left the future works, which are related with how the learning could be improved and what should be designed in the further research.

• Aerospace Engineering and Technology
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• v.3 no.2
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• pp.177-182
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• 2004

It is booming to use computer owing to the information society, and embedded software application have grown in airborne systems and equipment. So this introduces airborne software classification, software life cycle, activities to achieve objectives and software considerations in design and certification.