• Journal of Information Technology Services
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• 제16권4호
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• pp.161-176
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• 2017

Recently, most of the users can easily get access to a variety of information sources about companies, products, and services through online channels. Therefore, the online user evaluations are becoming the most powerful tool to generate word of mouth. The user's evaluation is provided in two forms, quantitative rating and review text. The rating is then divided into an overall rating and a detailed rating according to various evaluation criteria. However, since it is a burden for the reviewer to complete all required ratings for each evaluation criteria, so most of the sites requested only mandatory inputs for overall rating and optional inputs for other evaluation criteria. In fact, many users input only the ratings for some of the evaluation criteria and the percentage of missed ratings for each criteria is about 40%. As these missed ratings are the missing values in each criteria, the simple average calculation by ignoring the average 40% of the missed ratings can sufficiently distort the actual phenomenon. Therefore, in this study, we propose a methodology to predict the rating for the missed values of each criteria by analyzing user's evaluation information included the overall rating and text review for each criteria. The experiments were conducted on 207,968 evaluations collected from the actual hotel evaluation site. As a result, it was confirmed that the prediction accuracy of the detailed criteria ratings by the proposed methodology was much higher than the existing average-based method.

• The Journal of the Convergence on Culture Technology
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• 제10권2호
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• pp.493-498
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• 2024

With the rapid advancement of generative artificial intelligence technology, there is growing interest in how to utilize it in practical applications. Additionally, the importance of prompt engineering to generate results that meet user demands is being newly highlighted. Exploring the new possibilities of generative AI can hold significant value. This study aims to utilize ChatGPT 4.0, a leading generative AI, to propose an effective method for evaluating user experience through the analysis of online customer review data. The user experience evaluation method was based on the six-layer elements of user experience: 'functionality', 'reliability', 'usability', 'convenience', 'emotion', and 'significance'. For this study, a literature review was conducted to enhance the understanding of prompt engineering and to grasp the clear concept of the user experience hierarchy. Based on this, prompts were crafted, and experiments for the user experience evaluation method were carried out using the analysis of collected online customer review data. In this study, we reveal that when provided with accurate definitions and descriptions of the classification processes for user experience factors, ChatGPT demonstrated excellent performance in evaluating user experience. However, it was also found that due to time constraints, there were limitations in analyzing large volumes of data. By introducing and proposing a method to utilize ChatGPT 4.0 for user experience evaluation, we expect to contribute to the advancement of the UX field.

• Journal of Information Technology Applications and Management
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• 제31권1호
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• pp.163-175
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• 2024

This study conducts topic modeling analysis on four electric scooter sharing platforms: Alpaca, SingSing, Kickgoing, and Beam. Using user review data, the study aims to identify key topics and issues associated with each platform, as well as uncover common themes across platforms. The analysis reveals that users primarily express concerns and preferences related to application usability, service mobility, and parking/accessibility. Additionally, each platform exhibits unique characteristics and challenges. Alpaca users generally appreciate convenience and enjoyment but express concerns about safety and service areas. SingSing faces issues with application functionality, while Kickgoing users encounter connectivity problems and device usability issues. Beam receives overall positive feedback, but users express dissatisfaction with application usability and parking. Based on these findings, scooter sharing service providers should focus on enhancing application features, stability, and expanding service coverage to meet user expectations and improve customer satisfaction. Furthermore, highlighting platform-specific strengths and providing tailored services can enhance competitiveness and foster continuous service growth and development.

• Journal of KIBIM
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• 제9권4호
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• pp.1-9
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• 2019

Visualized information platforms through building information modeling (BIM) such as virtual reality (VR) and augmented reality (AR) improves the efficiency of architectural information exchange. Despite that, less effort has been directed to evaluate the effectiveness of different BIM visualization platforms for architectural design review. This study fills these gaps and compares three BIM visualization tools for reviewing diverse architectural review factors and technology acceptance degree. Three main BIM visualization tools, which are desktop-based, virtual reality-based and augmented reality-based, were employed and different architectural review factors and user's technology acceptance degree was measured. As a result, VR and AR environment showed better visual presentation than desktop environment during design review. In terms of the technology acceptance level, VR and AR environments have received higher ratings compared to desktop environments. The detailed findings provide guidelines for participants and researchers involved in design review process to selectively adopt VR and AR system to various architectural design review components.

• Journal of Korea Society of Digital Industry and Information Management
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• 제19권1호
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• pp.91-107
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• 2023

With the recent expansion of the commerce ecosystem, a large number of user evaluations have been produced. Accordingly, attempts to create business insights using user evaluation data have been actively made. However, since user evaluation can change after the user experiences the product, it is difficult to say that the analysis based only on reviews immediately after purchase fully reflects the user's evaluation of the product. Moreover, studies conducted so far on user evaluation have overlooked the fact that the length of time a user has used a product can affect the user's product evaluation. Therefore, in this study, we build a model that predicts the direction of change in the user's rating after use from the user's rating and reviews immediately after purchase. In particular, the proposed model reflects the product's period of use in predicting the change direction of the star rating. However, since the posterior information on the duration of product use cannot be used as input in the inference process, we propose a structure that utilizes information about the product's period of use using an auxiliary classifier. As a result of an experiment using 599,889 user evaluation data collected from the shopping platform 'N' company, we confirmed that the proposed model performed better than the existing model in terms of accuracy.

• Journal of Korea Society of Digital Industry and Information Management
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• 제10권1호
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• pp.81-87
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• 2014

Password-based authentication using smart card provides two factor authentications, namely a successful login requires the client to have a valid smart card and a correct password. While it provides stronger security guarantees than only password authentication, it could also fail if both authentication factors are compromised ((1) the user's smart card was stolen and (2) the user's password was exposed). In this case, there is no way to prevent the adversary from impersonating the user. Now, the new technology of biometrics is becoming a popular method for designing a more secure authentication scheme. In terms of physiological and behavior human characteristics, biometric information is used as a form of authentication factor. Biometric information, such as fingerprints, faces, voice, irises, hand geometry, and palmprints can be used to verify their identities. In this article, we review the biometric-based authentication scheme by Cheng et al. and provide a security analysis on the scheme. Our analysis shows that Cheng et al.'s scheme does not guarantee any kind of authentication, either server-to-user authentication or user-to-server authentication. The contribution of the current work is to demonstrate these by mounting two attacks, a server impersonation attack and a user impersonation attack, on Cheng et al.'s scheme. In addition, we propose the enhanced authentication scheme that eliminates the security vulnerabilities of Cheng et al.'s scheme.

• The Journal of the Korea Contents Association
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• 제14권9호
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• pp.567-581
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• 2014

Recently, with the introduction of social network services, studies that try to make use of them for the various purposes have been actively developed. In order to proceed with the research that takes advantage of social network services, it is necessary to review the relevant literature and to identify trends in researches. However, the researches of social network service since 2007 are massive amount, so to review the huge amount of relevant research literature is a very difficult task. Therefore, in this study, we analyze systematically the tendency of research related to social network service focusing on Twitter. Especially, we use the SLR(Systematic Literature Review) technique for systematic literature survey and analysis. For the literature survey, we select five well-known literature resource sites and 128 studies of literature that are surveyed. In order to identify various research trends, we conduct the survey with two research groups: researches since 2007 and researches since 2011. As a result of the investigation, since 2007, the researches associated with "Application", "User Activity" and "User Content Analysis" main study topics have been mostly carried out. In addition to the result, the trend of secondary study topics in a main study topic, trends in research based on the number of citations and the scale of the experimental data and characteristics of the author are analyzed from a variety of perspectives.

• Journal of the Korean Society for information Management
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• 제39권3호
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• pp.311-336
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• 2022

This study analyzed the contents of Goodreads review data, which is a social cataloging service with the participation of book users around the world, to identify the preference factors that affect book users' book recommendations in the library information service environment. To understand user preferences from a more detailed point of view, sub-datasets for each rating group, each book, and each user were constructed in the sample selection process. Stratified sampling was also performed based on the result of topic modeling of review text data to include various topics. As a result, a total of 90 preference factors belonging to 7 categories('Content', 'Character', 'Writing', 'Reading', 'Author', 'Story', 'Form') were identified. Also, the general preference factors revealed according to the ratings, as well as the patterns of preference factors revealed in books and users with clear likes and dislikes were identified. The results of this study are expected to contribute to more sophisticated recommendations in future recommendation systems by identifying specific aspects of user preference factors.

• International Commerce and Information Review
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• 제10권3호
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• pp.59-73
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• 2008

The current research utilized as its target population who are current users of global small to medium sized companies in Korea. The research validated the innovative dimensions by studying the two constructs within the context of the SMB user population. Correlation was found between innovative dimensions retained as components of a Comprehensive Model. It was determined that these four dimensions-Content, Intrinsic Interest, Control, and Timeliness-are significant predictors of user success. The Comprehensive Model was validated, and it is therefore suggested as a basis for further study of user success indicators in the innovative manufacturing enterprise environment.

• Management & Information Systems Review
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• 제34권3호
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• pp.161-177
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• 2015

Currently, the influence of the Internet portal sites that can make it quick and easy to contact the vast amount of information is increasing. Users can connect the Internet through a portal to obtain information, such as communication between Internet users, which can be used to meet a variety of purposes. People are exposed to a variety of information from other users in the search for a movie and get information. The impact on the reviews and ratings with the limited number of characters of the film allows users to form a relationship to the movie, decide whether you want to see the movie or find another movie. but, the user can not read the whole movie review. When user see the overall evaluation, the user can receive the correct information. This research conducted a study on the prediction of the rating by the use of review data. Information of reviews, is divided into two main areas: the"fact" and "opinion". "Fact" is to convey the dispassionate information and "Opinion" is, to represent the user's feelings. In this study, we built sentiment dictionary based on the assessment and evaluation of the online review and applied to evaluate other movies. In the comparative study with a simple emotion evaluation technique, we found the suggested algorithm got the more accurate results.