• ETRI Journal
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• 제32권6호
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• pp.843-853
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• 2010

A successful deployment of multimedia applications over wireless environments entails improving the quality of service (QoS), not only from a technical point of view, but also considering the quality of experience (QoE) from the final user's perception. Although objective QoE measure models avoid the difficulties of subjective surveys, subjective QoE assessments are essential to understand the way users evaluate the QoS. In this work, we study the effect of a wide range of parameters on the QoE of VVoIP applications in a real wireless scenario. Through a complete statistical analysis of users' ratings, we identify the following facts. Although the use of VVoIP in wireless networks does not yet represent an advantage for users, there are great expectations for all applications under study, and with greater popularity comes higher expectations. It is easier for respondents to identify good behavior than poor behavior. Whereas the respondents' frequency of Internet use does not impact on the scores, respondents' gender does. Finally, the most determining parameters of quality from a user's perspective were instability, video quality, voice distortion, usefulness, and graphical interface.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.538-561
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• 2020

Recommender Systems (RecSys) have a major role in e-commerce for recommending products, which they may like for every user and thus improve their business aspects. Although many types of RecSyss are there in the research field, the state of the art RecSys has focused on finding the user similarity based on sequence (e.g. purchase history, movie-watching history) analyzing and prediction techniques like Recurrent Neural Network in Deep learning. That is RecSys has considered as a sequence prediction problem. However, evaluation of similarities among the customers is challenging while considering temporal aspects, context and multi-component ratings of the item-records in the customer sequences. For addressing this issue, we are proposing a Deep Learning based model which learns customer similarity directly from the sequence to sequence similarity as well as item to item similarity by considering all features of the item, contexts, and rating components using Dynamic Temporal Warping(DTW) distance measure for dynamic temporal matching and 2D-GRU (Two Dimensional-Gated Recurrent Unit) architecture. This will overcome the limitation of non-linearity in the time dimension while measuring the similarity, and the find patterns more accurately and speedily from temporal and spatial contexts. Experiment on the real world movie data set LDOS-CoMoDa demonstrates the efficacy and promising utility of the proposed personalized RecSys architecture.

• 대한산업공학회지
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• 제30권4호
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• pp.338-345
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• 2004

Personal Digital Assistants (PDAs) have become ubiquitous and continued to gain popularity. Since PDAs have some special contexts such as mobility and limited screen size, icons are utilized frequently because icons allow us to do tasks more rapidly and effectively on PDAs like another information appliances. The study presents a cognitive approach to study human factors affecting icon design with multidimensional Scaling (MDS) analysis. In the experiment, a real PDA was used to investigate 29 attributes and2 preference ratings for 22 PDA icons by 20 Korean subjects. As a result, cognitive positioning about icons, attributes, and preference data were arranged on the two dimensional perceptual map. Attributes were grouped by simplicity, universality, activity, complexity, abstraction, static, and alphanumeric time. Subjects preferences were highly related with simplicity attributes group and positive to universality and activity attributes groups. It was also confirmed that there are some icons unfitted to the mental model of Korean. However, when icons are designed for PDAs or similar information appliances to Korean, it should be designed simply and actively with universal image fitted on target users mental model.

• 한국조경학회지
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• 제22권3호
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• pp.29-40
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• 1994

The purpose of this study was to investigate factors and variables which have significant effects on satisfaction of urban pedestrian sidewalk in taejon city, and to suggest basic information for urban pedestrian sidewalk. These works consist of two phase; The first, tested the user's degree of satisfaction for 37 spots of pedestrian sidewalk slide and then selected 10 spots slide by the stratified random sampling method. The second, analyzed factors and variables of satisfaction of urban pedestrian sidewalk using the semantic differential scale method, and then processed by mean score, correlation, factor analysis, multiful algorithm. The results were summarized as follows; 1) The relationship between the man group and the woman group was highly correlated as well as between the student group.1 and the student group.2 hense these groups statistically showed no difference in satisfaction ratings. 2) Pedestrian sidewalk width, cleanness, pavement materials and construction condition can be significant variables of satisfaction of urban pedestrian sidewalk. 3) Factors covering the satisfaction of urban pedestrian sidewalk have been found to be Environment of pedestrian sidewalk, Vegetation of pedestrian sidewalk and Form of pedestrian sidewalk. By using the control method for the number of factors, C.P. has been obtained as 62.8%.

• 컴퓨터교육학회논문지
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• 제6권2호
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• pp.147-156
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• 2003

협업여과는 흥미 있어하는 제품이나 개인화된 자료, 항목을 제공하기 의해 전체 집단의 의견을 반영하는 전자상거래에서 일반적으로 이용되는 기술이다. 협업여과는 정확하고 신뢰할 수 있는 도구로 입증되어 여러 분야의 전자상거래 영역에서 활용되고 있으나 아직까지 교육분야에는 한정적으로 적용되고 있다. 본 논문에서는 교육용 컨텐츠 추천에 사용자의 평가 점수를 이용하는 협업여과 방식의 추천시스템을 설계하였으며, 사용자 정보를 이용하여 추천의 정확도를 향상시키기 위한 유사도 보정기법을 도입하였다. 평균절대오차(MAE)와 반응자작용특성(ROC)값을 이용하여 제안한 시스템이 기존의 협업여과방식보다 추천 효율이 우수함을 검증하였다.

• 한국IT서비스학회지
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• 제20권3호
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• pp.57-73
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• 2021

Recently, online job websites have been activated as unemployment problems have emerged as social problems and demand for job openings has increased. However, while the online job platform market is growing, users have difficulty choosing their jobs. When users apply for a job on online job websites, they check various information such as job contents and recruitment conditions to understand the details of the job. When users choose a job, they focus on various details related to the job rather than simply viewing and supporting the job title. However, existing online job websites usually recommend jobs using only quantitative preference information such as ratings. However, if recommendation services are provided using only quantitative information, the recommendation performance is constantly deteriorating. Therefore, job recommendation services should provide personalized services using various information about the job. This study proposes a recommended methodology that improves recommendation performance by elaborating on qualitative preference information, such as details about the job. To this end, this study performs a topic modeling analysis on the job content of the user profile. Also, we apply LDA techniques to explore topics from job content and extract qualitative preferences. Experiments show that the proposed recommendation methodology has better recommendation performance compared to the traditional recommendation methodology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권5호
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• pp.1708-1727
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• 2021

In the advent of the twenty-first century, human beings began to closely interact with technology. Today, technology is developing, and as a result, the world wide web (www) has a very important place on the Internet and the significant task is fulfilled by Web services. A lot of Web services are available on the Internet and, therefore, it is difficult to find matching Web services among the available Web services. The recommendation systems can help in fixing this problem. In this paper, our observation was based on the recommended method such as the collaborative filtering (CF) technique which faces some failure from the data sparsity and the cold-start problems. To overcome these problems, we first applied an ontology-based clustering and then the k-nearest neighbor (KNN) algorithm for each separate cluster group that effectively increased the data density using the past user interests. Then, user ratings were predicted based on the model-based approach, such as singular value decomposition (SVD) and the predictions used for the recommendation. The evaluation results showed that our proposed approach has a less prediction error rate with high accuracy after analyzing the existing recommendation methods.

• 한국BIM학회 논문집
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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.

• 한국콘텐츠학회논문지
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• 제14권11호
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• pp.628-643
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• 2014

이 연구는 지상파 라디오의 일부 프로그램에서 지상파를 이용한 실시간 이용자보다 스마트 폰 같은 새로운 기기를 통해 비선형적, 탈편성시간적으로 이용하는 사람들이 더 많아진 사례를 어떻게 해석할 것인가에 대한 질문으로부터 시작하였다. 스마트폰의 대중화 시대에 지상파 라디오 프로그램의 이용자들이 팟캐스팅이라는 새로운 서비스를 통해 오디오 콘텐츠를 어떤 유형으로 이용하는가를 Q방법론을 통해 탐색했다. 그 결과 세 가지의 서로 다른 이용에 대한 태도와 인식을 가진 집단으로 유형화되었다. 20세기 매스 커뮤니케이션을 가능케 한 대표적인 미디어 중 하나인 라디오 콘텐츠의 이용이 이미 전통적 이용행태 패턴을 벗어나는 이러한 주목할 만한 상황은, 지상파를 이용한 전통기기를 통한 청취라는, 탄생 이후의 오랜 관습에서 벗어나 스마트폰을 경유하여 기존 이용자층에 맞먹거나 그 보다 더 커진 새로운 이용자층을 만들어낼 가능성과 새로운 서비스로서의 팟캐스팅이 기존 라디오 콘텐츠를 대체할 가능성을 보여 준다.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 1부
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• pp.262-268
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• 2008

Recently, as the demand for multimedia services based on the wireless technologies and mobile devices increases, Full-touch screen mobile devices adopting touch screen keyboards are emerging to cope with the limited display size and take advantage of the flexibility in the design of user interfaces. However, the text entry task, which is one of the main features of the mobile devices, decreases the competitive advantages of the touch screen keyboards over the physical keyboards or keypads due to the lack of physical feedbacks and the frequent occurrence of mistyping. This study aims to introduce a novel text entry method named Fuzzy Touch and compare this method with the conventional text entry method on a touch screen keyboard in terms of the performance (time, number of touch) and the subjective ratings (ease of use, overall preference).