• Korean journal of communication and information
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• v.38
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• pp.119-146
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• 2007

The purpose of this paper is to explore the factors causing adolescents' habitual use of text-based online social interaction (TOSI). The authors of the present study assumed that adolescents' perceived intimacy would affect the use of TOSI. Using structural equation modeling, the influences of perceived social presence and Internet self-efficacy on habitual use of TOSI were examined indirectly as well as directly, with and without intimacy as a mediate factor. The results show that the indirect effects were proven to be stronger compared with the direct effects. Perceived intimacy appeared to encourage more frequent uses of TOSI. The effects of intimacy were even more stronger especially with those who had higher levels of Internet self-efficacy.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.226-228
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• 2002

본 논문에서는 실시간 대화 행위에서 대화 메시지 사이의 응답 관계를 시각적으로 표현하는 방법을 제안한다. 제안한 방법은 기존 텍스트 기반 대화 방식과 트리 기반 대화 방식을 결합한 형태로서 대화 메시지의 일반적인 응답 관계뿐만 아니라, 기존 트리 기반 인터페이스에서 지원이 어려운 최근 수신 대화 메시지의 응답 관계를 시각화함으로써 대화자의 상호작용을 용이하게 한다. 이러한 방법은 기존 텍스트 방식의 테이블 구조에 트리 구조를 결함하여 대화에서 응답 관계를 명확히 구분한다. 제안한 방법의 구현은 XML과 DOM을 이용하여 대화 메시지와 대화 시스템을 구현하였으며, 응용 분야는 협업, 원격 교육, 온라인 게임 등이다.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.91-98
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• 2004

This paper proposes how to support various media on online conversational activity using XML(extensible Markup Language). The method converts media information into XML based messages and handles alike conventional text based messages. The XML based messages are unified to an XML document, and then a HTML document is generated using the XML and an XSLT documents in a server. A user in each client can play or present media through the hyperlink that is associated media information on the HTML document. The suggested method supports use of various media (text, image, audio, video, documents, etc) and efficient maintenance of font size, color, and style on messages according to extension and modification of XML tags. For application, this paper implemented the system to support media that has client and server architecture on online conversational activity. A user in each client inputs text or media based message using JAVA applet and servlet on the system, and conversational messages on every users' interfaces are automatically updated whenever a user inputs new message. Media on conversational messages are played or presented according to a user's click on hyperlink. Applications for the media presentation are as follows : distance learning, online game, collaboration, etc.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.41-63
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• 2023

As the online e-commerce market growing, the need for a recommender system that can provide suitable products or services to customer is emerging. Recently, many studies using the sentiment score of online review have been proposed to improve the limitations of study on recommender systems that utilize only quantitative information. However, this methodology has limitation in extracting specific preference information related to customer within online reviews, making it difficult to improve recommendation performance. To address the limitation of previous studies, this study proposes a novel recommendation methodology that applies deep learning technique and uses various linguistic factors within online reviews to elaborately learn customer preferences. First, the interaction was learned nonlinearly using deep learning technique for the purpose to extract complex interactions between customer and product. And to effectively utilize online review, cognitive contents, affective contents, and linguistic style matching that have an important influence on customer's purchasing decisions among linguistic factors were used. To verify the proposed methodology, an experiment was conducted using online review data in Amazon.com, and the experimental results confirmed the superiority of the proposed model. This study contributed to the theoretical and methodological aspects of recommender system study by proposing a methodology that effectively utilizes characteristics of customer's preferences in online reviews.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.171-189
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• 2022

Online reviews play an essential role in the consumer's purchasing decision-making process, and thus, providing helpful and reliable reviews is essential to consumers. Previous online review helpfulness prediction studies mainly predicted review helpfulness based on the consistency of text and rating information of online reviews. However, there is a limitation in that representation capacity or review text and rating interaction. We propose a CNN-RHP model that effectively learns the interaction between review text and rating information to improve the limitations of previous studies. Multi-channel CNNs were applied to extract the semantic representation of the review text. We also converted rating into independent high-dimensional embedding vectors representing the same dimension as the text vector. The consistency between the review text and the rating information is learned based on element-wise operations between the review text and the star rating vector. To evaluate the performance of the proposed CNN-RHP model in this study, we used online reviews collected from Amazom.com. Experimental results show that the CNN-RHP model indicates excellent performance compared to several benchmark models. The results of this study can provide practical implications when providing services related to review helpfulness on online e-commerce platforms.

• Journal of The Korean Association of Information Education
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• v.14 no.1
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• pp.13-23
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• 2010

In recent creativity becomes a new request in the knowledge and information age. Robot programming education is an effective teaching method for improvement of creativity. Existing robot programming tools includes text-based or GUI-based development environment. Most of programming tools provide a simple tutorial system without interactive activity for beginners. In this paper, we propose an online robot programming education system based on web2.0, which embedded collaborative code creating tool, interactive tutorial chat and video conference tool to support collaborative code creating via web 2.0. Knowledge sharing tool allows users to share their collaborative source code. Besides, it makes users gained the experience and knowledge of program designing efficiently.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1579-1581
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• 2011

페이스북(Facebook)과 트위터(Twitter)등으로 각광 받는 소셜 네트워크 서비스(Social Network Service)는 사용자의 온라인과 오프라인에 구축된 인맥 네트워크를 기반으로 한다. SNS내의 소셜커머스, 소셜어플리케이션 등의 다양한 기능이 추가 되면서 새로운 온라인 서비스 시장이 등장하게 되었다. 초기의 새로운 가상 인맥 늘리기 수단으로 사용되었던 SNS서비스는 스마트폰의 등장과 카메라, 마이크 등의 추가 디바이스와 서비스간의 연계가 가능해 지면서 이용자들의 새로운 정보 생성과 실시간 커뮤니케이션이 가능해 졌다. 또한 SNS를 통한 정보의 흐름은 텍스트 기반의 한방향 정보 전달 틀에서 소리와 이미지, 동영상등의 다양한 미디어가 취합되는 공간이 됨으로서 사용자와 다른 사용자간의 상호 작용이 가능한 쌍방향 소통으로 현실의 정보를 보다 정확하고 빠르게 전달할 수 있는 하나의 미디어 형태로 진화하는 중이다. 본 논문에서는 소셜 서비스에서 생성된 정보가 집단 협업(Mass Collaboration)을 이룰 때 갖는 신뢰성을 기대하여 키워드 중심의 정보 형성에 따른 SNS 활용 방법을 제시한다.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.31-49
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• 2023

With the growth of the food-catering industry, consumer preferences and the number of dine-in restaurants are gradually increasing. Thus, personalized recommendation services are required to select a restaurant suitable for consumer preferences. Previous studies have used questionnaires and star-rating approaches, which do not effectively depict consumer preferences. Online reviews are the most essential sources of information in this regard. However, previous studies have aggregated online reviews into long documents, and traditional machine-learning methods have been applied to these to extract semantic representations; however, such approaches fail to consider the surrounding word or context. Therefore, this study proposes a novel review textual-based restaurant recommendation model (RT-RRM) that uses deep learning to effectively extract consumer preferences from online reviews. The proposed model concatenates consumer-restaurant interactions with the extracted high-level semantic representations and predicts consumer preferences accurately and effectively. Experiments on real-world datasets show that the proposed model exhibits excellent recommendation performance compared with several baseline models.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.155-161
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• 2022

The outbreak of the Covid 19 increased the interest on the 'Virtual Tourism. In this research the key word related to "Virtual Tourism" was collected through the search engine and was analyzed through the data mining method such as Log-odds ratio, Frequency, and network analysis. It is clear that the information and communication dependency increased in the field of "Virtual Tourism" after Covid 19 and also the trend have changed from "securement of the contents diversity" to "project related to economic recovery." Since the demands for the "Virtual Reality" such as metaverse is increasing, there should be an economic and circular structure in which the government establishing a related policy and the funding plan based on the research, local government and the private companies planning and producing discriminate contents focusing on AISAS(Attension, Interest, Search, Action, Share) aand the research institutions and universities developing, applying, assessing and commercializing the technology.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.205-210
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• 2024

Nowadays, online messengers are the main communication tool of modern people. Currently, not only messengers that communicate based on text and images, but also services that can interact in real time through voice or screen sharing are actively used by the MZs. This study aims to figure out 1) the motivation of users of voice chat services, and 2) to explore the influence of motivation for use on satisfaction that one of the factors that determine the user's experience. As a result, five major motivations for using voice chat service(Relationship formation, Usefulness, Relationship maintenance, communication supplementation, and distance overcoming) were found. Among them 'Usefulness' and 'Relationship maintenance had a positive effect on user satisfaction. This study, highlighted the various needs of users who communicate in a non-face-to-face environments as well as factors to be satisfied for their positive experiences. These results should be actively used in the online communications market.