• Journal of Digital Contents Society
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• v.16 no.5
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• pp.681-689
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• 2015

This study aims to survey the effectiveness of the international distance learning between Korean and Japanese university students. This research is based on NWCCDL (Namseoul-Waseda Cross-Cultural Distance Learning) project in the spring semester, 2015. This project is the cross-cultural distance learning project between N University in Korea and W University in Japan, and the most important thing of this project is that this project is manipulated through the utilization of ICT. This research consists with two parts: the first is to introduce the NWCCDL project; the participants' information, and the contents and procedure of the on-line chatting program, and BBS(Bulletin Board System) activities. The second is to review on the students' satisfaction for the project and the utilization of ICT in English language education context. The analytic results of the questionnaire includes the students' satisfaction on this project and their reflection on the effectiveness of using ICT in English language classroom of Korea. The results prove that the most of the students are satisfied with the NWCCDL Project in the spring semester, 2015 and the most of the students agree with the fact that the utilization of ICT is very effective in English language education of Korea.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.652-657
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• 2018

With the rapid development of e-commerce, many customers can now express their opinion on various kinds of product at discussion groups, merchant sites, social networks, etc. Discerning a consensus opinion about a product sold online is difficult due to more and more reviews become available on the internet. Opinion Mining, also known as Sentiment analysis, is the task of automatically detecting and understanding the sentimental expressions about a product from customer textual reviews. Recently, researchers have proposed various approaches for evaluation in sentiment mining by applying several techniques for document, sentence and aspect level. Aspect-based sentiment analysis is getting widely interesting of researchers; however, more complex algorithms are needed to address this issue precisely with larger corpora. This paper introduces an approach of knowledge representation for the task of analyzing product aspect rating. We focus on how to form the nature of sentiment representation from textual opinion by utilizing the representation learning methods which include word embedding and compositional vector models. Our experiment is performed on a dataset of reviews from electronic domain and the obtained result show that the proposed system achieved outstanding methods in previous studies.

• Journal of Korea Game Society
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• v.19 no.5
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• pp.103-114
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• 2019

We have been studying a deep-learning program that can communicate with other users in online communities since 2017. But there were problems with processing a Korean data set because of Korean characteristics. Also, low usage of GPUs of RNN models was a problem too. In this study, as Natural Language Processing models are improved, we aim to make better results using these improved models. To archive this, we use a Transformer model which includes Self-Attention mechanism. Also we use MeCab, korean morphological analyzer, to address a problem with processing korean words.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.120-128
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• 2023

In this work, we have presented ATSA, a hierarchical attention deep learning model for Arabic sentiment analysis. ATSA was proposed by addressing several challenges and limitations that arise when applying the classical models to perform opinion mining in Arabic. Arabic-specific challenges including the morphological complexity and language sparsity were addressed by modeling semantic composition at the Arabic morphological analysis after performing tokenization. ATSA proposed to perform phrase-chunks sentiment embedding to provide a broader set of features that cover syntactic, semantic, and sentiment information. We used phrase structure parser to generate syntactic parse trees that are used as a reference for ATSA. This allowed modeling semantic and sentiment composition following the natural order in which words and phrase-chunks are combined in a sentence. The proposed model was evaluated on three Arabic corpora that correspond to different genres (newswire, online comments, and tweets) and different writing styles (MSA and dialectal Arabic). Experiments showed that each of the proposed contributions in ATSA was able to achieve significant improvement. The combination of all contributions, which makes up for the complete ATSA model, was able to improve the classification accuracy by 3% and 2% on Tweets and Hotel reviews datasets, respectively, compared to the existing models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3868-3888
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• 2022

A widely used social networking service like Twitter has the ability to disseminate information to large groups of people even during a pandemic. At the same time, it is a convenient medium to share irrelevant and unverified information online and poses a potential threat to society. In this research, conventional machine learning algorithms are analyzed to classify the data as either non-rumor data or rumor data. Machine learning techniques have limited tuning capability and make decisions based on their learning. To tackle this problem the authors propose a deep learning-based Rumor Detection Neural Network model to predict the rumor tweet in real-world events. This model comprises three layers, AttCNN layer is used to extract local and position invariant features from the data, AttBi-LSTM layer to extract important semantic or contextual information and HPOOL to combine the down sampling patches of the input feature maps from the average and maximum pooling layers. A dataset from Kaggle and ground dataset #gaja are used to train the proposed Rumor Detection Neural Network to determine the veracity of the rumor. The experimental results of the RDNN Classifier demonstrate an accuracy of 93.24% and 95.41% in identifying rumor tweets in real-time events.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.11-24
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• 2022

For the questions asked for LMS-based online evaluation the professor directly set exam questions, or use the automatic question-taking method according to the level of difficulty using the question bank divided by category. Among them, it is important to manage the difficulty of questions in an objective and efficient way, above all, in the automatic question-taking method according to difficulty. Because the questions presented to the evaluators may be different. In this paper, we propose an difficulty re-adjustment algorithm that considers not only the correct rate of a problem but also the time taken to solve the problem. For this, a logistic regression classification algorithm was used of machine learning, and a reference threshold was set based on the predicted probability value of the learning model and used to readjust the difficulty of each item. As a result, it was confirmed that there were many changes in the difficulty of each item that depended only on the existing correct rate. Also, as a result of performing group evaluation using the adjustment difficulty problem, it was confirmed that the average score improved in most groups compared to the difficulty problem based on the percentage of correct answers.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.25-31
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• 2018

Online news has replaced the traditional newspaper and has brought about a profound transformation in the way we access and share information. News websites have had the ability for users to post comments for quite some time, and some have also begun to crowdsource reactions to news articles. The field of sentiment analysis seeks to computationally model the emotions and reactions experienced when presented with text. In this work, we analyze more than 100,000 news articles over ten categories with five user-generated emotional annotations to determine whether or not these reactions have a mathematical correlation to the news body text and propose a simple sentiment analysis algorithm that requires minimal preprocessing and no machine learning. We show that it is effective even for a morphologically complex language like Korean.

• Koreanishche Zeitschrift fur Deutsche Sprachwissenschaft
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• v.3
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• pp.327-346
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• 2001

Das Ziel dieser Arbeit liegt darin, den Bestand der wissenschaftlichen Web-Publikationen in der deutschen Linguistik darzustellen. Das Internet bietet heute $f\"{u}r$ die Forschung bereits zwei der wichtigsten produktiven $M\"{o}glichkeiten;n\"{a}mlich$ Information und Kommunikation. Akademische Kreise haben diverse Homepages entwickelt. Der schnelle Zugang zu aktuellen bibliographischen Daten und Forschungsergebnissen hat $f\"{u}r$ koreanische Germanisten einen besonders hohen Stellenwert. Wissenschaftliches Publizieren in Form von Fachzeitschriften ist ein gutes Modell $daf\"{u}r$. Fachzeitschriften erscheinen weltweit und relativ schnell, erreichen aber nur geringe Auflagen. Der Leserkreis ist fast identisch mit der Gruppe der potentiellen Autoren und Herausgeber. Ein Vorteil des elektronischen Publizierens ist die M\"{o}glichkeit$ multimeiale Dokumente und $weiterf\"{u}hrende$ Hyperlinks zu integrieren. Aber die $Qualit\"{a}t\;der\;Aufs\"{a}tze$ kann man kaum objektiv ermitteln und nur schwer beurteilen. Elektronische Zeitschriften $k\"{o}nnen$ sich in der Wissenschaft nur dann etablieren, wenn es gelingt, als wissenschaftliche Arbeiten von den wissenschaftlichen Kreisen oder von der Univerwaltung anerkannt zu werden. Folgende on-line wissenschaftliche Fachzeitschriften werden hier dargestellt; Linguistik online(ISSN 1615-3014), The Web Journal of Modern Language Linguistics(ISSN 1461-4499), PhiN(ISSN 1433-7177), Zeitschrift $f\"{u}r$ interkulturellen Fremdsprachenunterricht(ISSN: 1205-6545), und Language Learning & Technology(ISSN 1094-3501). 1)http://viadrina.euv-frankfurt-o.de/$\~wjoumal/deutsch/$ 2)http://wjmll.ncl.ac.uk/ 3)http://www.fu-berlin.de/phin/ 4)http://www.ualberta.ca/$\~german/ejoumal/$ 5)http://llt.msu.edu/ In der folgenden Homepage kann man auch eine Quellensammlung zu 'Dissertationen Online' finden. 6) http://www.educat.hu-berlin.de/$diss\_online/biblio.html$ Eine individuelle und institutionelle Offenheit und eine $n\"{u}chteme$ Anwendung der Materialien sind bei der Herstellung und Nutzung von Forschungsergebnissen erforderlich.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.548-566
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• 2013

The availability of technology and the abundance of experts in universities create an ample opportunity to provide a venue that allows a knowledge seeker to easily connect with and request advice from university experts. On the other hand, outsourcing provides opportunities and remains one of the emerging trends in organizations, and can very clearly observed in the Philippines. This paper describes the development of a reliable web-based approach to Knowledge Product Outsourcing (KPO) services in the Silliman Online University Learning system. The system is called an "e-Knowledge Box."It integrates Web 2.0 technologies and mechanisms, such as instant messaging, private messaging, document forwarding, video conferencing, online payments, net meetings, and social collaboration together into one system. Among the tools used are WAMP Server 2.0, PHP, BlabIM, Wordpress 3.0, Video Whisper, Red5, Adobe Dreamweaver CS4, and Virtual Box. The proposed system is integrated with the search engine in URLs, Web feeds, email links, social bookmarking, search engine sitemaps, and Web Analytics Direct Visitor Reports. The site demonstrates great web usability and has an excellent rating in functionality, language and content, online help and user guides, system and user feedback, consistency, and architectural and visual clarity. Likewise, the site was was rated as being very good for the following items: navigation navigation, user control, and error prevention and correction.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.109-116
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• 2021

Traditionally, the engineering field has been dominated by face-to-face education focused on experimental practice, but demand for online learning has soared due to the rapid development of IT technology and Internet communication networks and recent changes in the social environment such as COVID-19. In order for efficient online education to be conducted in the engineering field, where the proportion of experimental practice is relatively high compared to other fields, virtual laboratory practice content that can replace actual experimental practice is very necessary. In this study, we developed a line tracer model and a virtual experimental software to simulate it for efficient online learning of microprocessor applications that are essential not only in the electric and electronic field but also in the overall engineering field where IT convergence takes place. In the developed line tracer model, the user can set various hardware parameter values in the desired form and write the software in assembly language or C language to test the operation on the computer. The developed line tracer virtual experimental software has been used in actual classes to verify its operation, and is expected to be an efficient virtual experimental practice tool in online non-face-to-face classes.