• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.7
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• pp.1346-1367
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• 2011

As the size of camera modules is decreasing and as the computing performance of portable devices is improving, taking photos has become a part of daily life. However, existing photo management programs and products that manage such photos still require extensive user effort to facilitate the sharing and browsing of images. It is especially difficult for novice users to manage and share photos. In this paper, we develop a round-robin concept-driven user preference feedback mechanism for achieving direct photo sharing, instant display, and easy management using optimized user controls and user preference-driven classification. Compared with commercial photo management systems, our proposed solution provides new features: optimized user controls, direct sharing and instant display, and user preference feedback driven classification. These new features boost the round-robin concept-driven user preference feedback. This paper proposes a photo finder that automatically searches for photos in storage spaces or cameras. The proposed photo finder relies on user preference feedback to share photos by leveraging user preferences, and the round-robin connection transmits photos to the family's digital photo frame or web album by arbiter. The proposed method saves time and spares users the effort required for photo management. Moreover, this method does not merely direct photo sharing and simple photo management, but it also increases the satisfaction level of users viewing the photos.

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.3
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• pp.791-803
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• 2015

This study aims to examine the influence of tennis instructors' coaching behaviors on the satisfaction with lessons and preference for instructors. In order to achieve this study objective, by using the quota sampling out of nonprobability sampling for tennis club members who are now(2015) actively involved in tennis courts located in Daejeon Metropolitan City and Chungcheongnam-do, and also receiving tennis lesson for more than six months or used to take lessons before, the 325 effective samples were used for data analysis. Using the SPSS Ver. 21.0 Window Program, the collected data went through frequency analysis, exploratory factor analysis, reliability analysis, t-test, one-way ANOVA, correlation analysis and multiple regression analysis, and the results are like below. Regarding differences of coaching behaviors depending on sex, first, there were significant differences in the factors like explanatory instruction, positive feedback and negative feedback. In case of differences in accordance with age, every factor showed significant differences. In regard of differences depending on academic background, there were differences in the factor of negative feedback while the factor of positive feedback showed differences in accordance with the experience of lesson. In case of differences depending on the level of athletic performance, there were statistically significant differences in the factors like explanatory instruction, questioning instruction and negative feedback. Second, the positive feedback, one of the sub-factors of coaching behaviors had positive influence on satisfaction with lesson while the explanatory instruction, one of the sub-factors of coaching behaviors had positive influence on preference for instructors. Lastly, the satisfaction with lesson had positive influence on preference for instructors.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.641-642
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• 2008

In this paper, we propose a new approach for the implicit rating algorithm of finding user's intense and preference to the contents on the web. Although the explicit method dig out the user preference of specific contents based on the user's intervention, we propose the implicit method obtaining the user preference according to the user's behavioral patterns on the web implicitly and automatically without the user's intervention. The implementation results show that the proposed approach is highly valuable for supporting recommender systems in conjunction with the users lifestyle.

• English Language & Literature Teaching
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• v.16 no.1
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• pp.19-40
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• 2009

Teacher written feedback on student compositions has received tremendous attention in second language (L2) writing research. Notwithstanding the importance of understanding both teachers' and students' perspectives on the feedback process, much of the feedback research has only looked into one-side of the story - adopting either the teacher's or the student's perspective. The current study is an attempt to look into both sides of the story by examining the types of written feedback that students prefer, the extent to which students' preferences and teachers' actual feedback practice overlap, and the extent to which student perceptions of teacher feedback coordinate teacher self-reflections on their feedback practice. Three English composition classes (3 teachers and 46 students) at a university participated in this study. It analyzed student and teacher data from questionnaires and teacher written feedback on student compositions. The results showed that students' preference for feedback on global and local issues varied across the three composition classes. This is partly a consequence of how students perceived the type of feedback that their teachers practiced. Teacher self-reflection on and student perception of teacher written-feedback generally coordinated. These findings are discussed in light of how contextual factors affect learner perception of teacher written feedback and underscore the need for examining students' reactions to feedback and teacher self-reflection.

• English Language & Literature Teaching
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• v.15 no.4
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• pp.237-264
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• 2009

The present study explores patterns of teachers' corrective feedback and learners' uptake in Korean EFL undergraduate classroom setting. It also examines consistencies and discrepancies in the perception of corrective feedback by teachers and learners. Teachers' and learners' preferences and perception of corrective feedback are further analyzed to determine whether or not those differ from actual practices in English language learning classrooms. The results of the study are as follows. First of all, teachers' corrective feedback type varied according to the learners' error type and English proficiency level. There was a lack of consistency between the teachers' feedback practices and the learners' error types. Second, for the phonological errors, learners' data witnessed the most frequent uptake on recast. For the other error types, however, the learners' uptake rates were high for the explicit corrective feedback. Third, the teachers' explicit knowledge of corrective feedback was rather low and the preferences differed from teacher to teacher. The teachers' feedback perception and preferences did not consistently reflect their actual practices. Finally, patterns of the learners' expectations of corrective feedback varied according to learners' proficiency level. Teachers' and learners' expectations of corrective feedback were also compared and some mismatches were detected.

• Journal of Korea Multimedia Society
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• v.17 no.11
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• pp.1286-1295
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• 2014

This paper suggests the way that it could improve the reliability about preference of user's feedback by adding weighting factor on sentiment analysis, and efficiently make a sentiment analysis of users' emotional perspective on the big data massively generated on twitter. To solve errors on earlier studies, this paper has improved recall and precision of sensibility determination by using sensibility dictionary subdivided sentiment polarity based on the level of sensibility and given impotance to sensibility determination by populating slang, new words, emoticons and idiomatic expressions not in the system dictionary. It has considered the context through conjunctive adverbs fixed in korean characteristics which are free to the word order. It also recognize sensibility words such as TF(Term Frequency), RT(Retweet), Follower which are weighting factors of preference and has increased reliability of preference analysis considering weight on 'a very emotional tweet', 'a recognised tweet from users' and 'a tweeter influencer'

• Database Research
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• v.34 no.3
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• pp.86-98
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• 2018

Point-of-Interest(POI) recommendation systems suggest the most interesting POIs to users considering the current location and time. With the rapid development of smartphones, internet-of-things, and location-based social networks, it has become feasible to accumulate huge amounts of user POI visits. Therefore, instant recommendation of interesting POIs at a given time is being widely recognized as important. To increase the performance of POI recommendation systems, several studies extracting users' POI sequential preference from POI check-in data, which is intended for implicit feedback, have been suggested. However, when constructing a model utilizing sequential preference, the model encounters possibility of data distortion because of a low number of observed check-ins which is attributed to intensified data sparsity. This paper suggests refinement of temporal intervals based on data confidence. When building a POI recommendation system using temporal intervals to model the POI sequential preference of users, our methodology reduces potential data distortion in the dataset and thus increases the performance of the recommendation system. We verify our model's effectiveness through the evaluation with the Foursquare and Gowalla dataset.

• Science of Emotion and Sensibility
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• v.12 no.4
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• pp.531-544
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• 2009

In the past, objective usability was one of the most important aspects when user used system. But nowadays user's subjective experiences are getting more critical element than objective usability in HCI(human-computer interaction). Most people own their mobile phone and use it frequently these days. It is especially important to make user's subjective experiences more positive when using devices like mobile phones people frequently carry and interact with. This study investigates whether the interfaces which express the emotion give more positive experiences to users. Researchers created mobile phone prototypes to compare the effect of mechanical melody feedback(the major auditory feedbacks on mobile phones) and emotional voice feedback(recorded human voice). Participants experienced four kinds of mobile phone prototypes(no feedback, mechanical melody feedback, emotional voice feedback and dual feedback) and evaluated their experienced usability, hedonic quality and preference. The result suggests that person's perceptional fun and hedonic quality were getting increased in the phone which gave the emotional voice feedback than the mechanical melody feedback. Nevertheless, the preference was evaluated lower in the emotional voice feedback condition than the others.

• Journal of the Korea Society of Computer and Information
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• v.20 no.8
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• pp.93-104
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• 2015

In this paper, the design of intelligent_advertisement_operation system(IAdOS) based on user's feedback is proposed for mobile environments. The proposed system stores the advertising contents created by the advertising provider and recommends the personalized advertising contents by analyzing the context information, and then feedback information of the advertisements. Since the proposed system which can recommends provide the smart advertisement contents based on personal preference, it is expected to contribute the new service model development of in the field of advertising market.

• Journal of Technologic Dentistry
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• v.46 no.3
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• pp.126-132
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• 2024

Purpose: This study aims to examine the impact of instructor-learner interaction on online class satisfaction, perceived academic achievement, and online class preference. Methods: From December 20, 2023, to February 10, 2024, this study surveyed students in the medical and public health departments of K University and D University located in Gangwon-do and Daejeon, respectively. Results: In the online class environment, instructor-learner interaction showed a significant positive correlation with online class satisfaction, academic achievement, and online class preference. On re-examination using regression analysis, it was found that among the subfactors of instructor-learner interaction, instructional support and instructor presence had a significant impact. Conclusion: The findings suggest that in an online learning environment, instructors must make efforts to help learners identify what they need to learn by repeatedly asking whether they understand the learning content and providing appropriate feedback.