• Design Convergence Study
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• v.17 no.1
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• pp.17-28
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• 2018

The manipulation of the device by hand while driving is a major factor to increase the risk of accidents, and the design of in-vehicle voice conversational interface that can compensate for this is being actively researched. The purpose of this study is to investigate the effect of the use of the barge-in function of in-vehicle voice interface on user experience. Participants were asked to carry out two tasks, one for navigation and one for music play. We conducted a survey to measure the functional user 's experience after each participant' s tasks, and measured usefulness, usability, satisfaction, and emotion as user experience factors. As a result, Barge-in has been rated as the better choice for most experience factors. There was a significant effect on usability dimension in navigation task and significant effects on usability dimension and emotional dimension in music play task. So it was found that barge-in function had a positive effect on actual user's usability and emotional dimension.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.167-177
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• 2012

Recently, with the rapid development of information technology the field of e-book market is growing rapidly. The choice of an e-book device to improve user's comprehension is one of very important elements. The effectiveness evaluation between e-books and paper books has been studied previously, but there have not been progressed actively researches on the size of e-book devices based on user's comprehension. Considering these aspects, we in this paper selected e-book devices such as currently available PDA, netbook, and notebook, and then carried out the experiment about which device has the highest user's comprehension depending on the size of e-book devices. Understanding and memory about the content on the display were set as main factors in order to evaluate user's comprehension. We prepared in advance multiple examples of e-books and English words with similar difficulty, and evaluated user's comprehension through answering questions for each example after doing the experiment. 90 undergraduate students who use most widely e-books participated in the experiment, and the result was analyzed using SPSS statistical package. The experiment result showed that user's comprehension was higher in e-book device with middle size rather than the one with big size in display size.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.267-272
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• 2009

Video digests provide an effective way of confirming a video content rapidly due to their very compact form. By watching a digest, users can easily check whether a specific content is worth seeing in full. The impression created by the digest greatly influences the user's choice in selecting video contents. We propose a novel method of automatic digest creation that evokes a joyful impression through the created digest by exploiting smile/laughter facial expressions as emotional cues of joy from video. We assume that a digest presenting smiling/laughing faces appeals to the user since he/she is assured that the smile/laughter expression is caused by joyful events inside the video. For detecting smile/laughter faces we have developed a neural network based method for classifying facial expressions. Video segmentation is performed by automatic shot detection. For creating joyful digests, appropriate shots are automatically selected by shot ranking based on the smile/laughter detection result. We report the results of user trials conducted for assessing the visual impression with automatically created 'joyful' digests produced by our system. The results show that users tend to prefer emotional digests containing laughter faces. This result suggests that the attractiveness of automatically created video digests can be improved by extracting emotional cues of the contents through automatic facial expression analysis as proposed in this paper.

• Proceedings of the Safety Management and Science Conference
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• 2008.04a
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• pp.157-179
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• 2008

This study demonstrates some major traits of digital contents as information, playfulness, individuality, perceived recognition as perceived usefulness and perceived ease of use, relationship quality as satisfaction and commitment, user behavior as use intention. To make an empirical analysis the study, it is hypothesized that traits of digital contents and perceived recognition, traits of digital contents and relationship quality, perceived recognition and relationship quality, relationship quality and user behavior. Proposed theoretical model was based on TAM and was tested by the structure equation model for validity, credibility, goodness of fit. The major finding of this study can be summarized as follows, traits of digital contents are positively affected by perceived recognition, satisfaction in relationship quality and use intention via perceived recognition. Theoretical implication of this study are as follows. First, users wanted to choice only needed information. Second, users recognized digital contents as a part of life. So, user's ability is very important in this environment. According to this, business related with or interested in digital contents must have developed digital contents in variety aspect. Users must have concerned using digital contents, also.

• Proceedings of the ESK Conference
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• 1995.10a
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• pp.240-248
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• 1995

In Korea, it is not satisfactory in the product design since Kansei engineering or Ergnomics is not very active and well considered. When designing a mini-component, the user's emotion was not considered well. It is typical to have a rectangular shape, dark- colored outside in a mini-component design. Therefore, the users have to select with available choice from the manufacture's traditional designs. In this study, a new smin- component was designed to be suitable for a new generation's (10 to mid-20) sensation. First of all, an ergonomic problems were investigated. And then, the survey was per- formed to consider the emotion of the new generation. After that, the new design was made to reflect the new generation's trend and preference. In addition, the high-touch (human-centered design) and human touch (the product to give a sensible satisfaction for human) concepts were added.

• Journal of Digital Contents Society
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• v.11 no.4
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• pp.473-478
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• 2010

Applying ubiquitous computing technology continues to develop services and to use it also has developed a variety of devices. However, classification of ubiquitous computing service (UCS) is ambiguous and evaluation criteria of UCS are difficult to be applied. In this paper, we define the characteristics and classification of UCS and based on evaluation criteria are derived. In addition, we propose a checklist of evaluation criteria to support the user's choice using UCS.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.95-102
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• 2012

Interactive drama is a story which requires user's free choice and participation. In this study, we grasp user's preference by making training data that utilize characters of interactive drama. Furthermore, we describe process of implementing systems which recommend new users path of stories that correspond with their preference. We used PCA and NMF to extract characteristic of preference. The success rate of recommending was 75% with PCA, while 62.5% with NMF.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.520-541
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• 2023

In CRNs, SS is of utmost significance. Every CR user generates a sensing report during the training phase beneath various circumstances, and depending on a collective process, either communicates or remains silent. In the training stage, the fusion centre combines the local judgments made by CR users by a majority vote, and then returns a final conclusion to every CR user. Enough data regarding the environment, including the activity of PU and every CR's response to that activity, is acquired and sensing classes are created during the training stage. Every CR user compares their most recent sensing report to the previous sensing classes during the classification stage, and distance vectors are generated. The posterior probability of every sensing class is derived on the basis of quantitative data, and the sensing report is then classified as either signifying the presence or absence of PU. The ISVM technique is utilized to compute the quantitative variables necessary to compute the posterior probability. Here, the iterations of SVM are tuned by novel GO-PSA by combining GOA and PSO. Novel GO-PSA is developed since it overcomes the problem of computational complexity, returns minimum error, and also saves time when compared with various state-of-the-art algorithms. The dependability of every CR user is taken into consideration as these local choices are then integrated at the fusion centre utilizing an innovative decision combination technique. Depending on the collective choice, the CR users will then communicate or remain silent.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.18-24
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• 2010

Mobile devices wide spread among users after the release of Apple's iPhone, especially in Korea. Mobile device has their own advantages in terms of weight, size, mobility and so on. But, on the contrary, mobile device has to provide more accurate and personalized information because of a small screen and a limited function of information retrieval. This paper presents a user"s preference element changeable recommender system by employing extended collaborative filtering as a technique to provide useful information in a mobile environment. Proposed system reflects user's similar groups by simultaneously considering users' information with preferences and demographic characteristics. Then we construct list of recommenders by user's choice. Finally, we show the implementation of a prototype based on iPhone.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.59-68
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• 2022

A recommender system covers users, searches the items or services which users will like, and let users purchase them. Because recommendations from a recommender system are predictions of users' preferences for the items which they do not purchase yet, it is rarely possible to be drawn a perfect answer. An evaluation has been conducted to determine whether a prediction is right or not. However, it can be lower user's satisfaction if a recommender system focuses on only the preferences, that is caused by a 'filter bubble effect'. The filter bubble effect is an algorithmic bias that skews or limits the information an individual user sees on the recommended list. It is the reason why multiple metrics are required to evaluate recommender systems, and a diversity metrics is mainly used for it. In this paper, we compare three different methods for enhancing diversity for personalized recommendation - bin packing, weighted random choice, greedy re-ranking - with a practical e-commerce data acquired from a fashion shopping mall. Besides, we present the difference between experimental results and F1 scores.