• Title/Summary/Keyword: Contents Preference

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Driver Preference Based Traffic Information Recommender Using Context-Aware Technology (상황인식 기술을 이용한 운전자 선호도 기반 교통상세정보 추천 시스템)

  • Sim, Jae Mun;Kwon, Ohbyung;Kang, Ji Uk
    • Knowledge Management Research
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    • v.11 no.2
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    • pp.75-93
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    • 2010
  • Even though there have been many efforts on driver's route recommendation, driver still should get involved to choose the driving path in a manual manner. Uncertain traffic information provided to the driver delays his arrival time and hence may cause diminished economic values. One of the solutions of reducing the uncertainty is to provide various kinds of traffic information, rather than send real-time information. Therefore, as the wireless communication technology improves and at the same time volume of utilizable traffic contents increases in geometrical progression, selecting traffic information based on driver's context in a timely and individual manner will be needed. Hence, the purpose of this paper is to propose a methodology that efficiently sends the rich traffic contents to the personal in-vehicle navigation. To do so, driver preference is modeled and then the recommendation algorithm of traffic information contents was developed using the preference model. Secondly, ontology based traffic situation analyzation method is suggested to automatically inference the noticeable information from the traffic context on driver's route. To show the feasibility of the idea proposed in this paper, an open API service is implemented in consideration of ease of use.

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Implementation of SIP-based Extended Caller Preference in VoIP System (VoIP 시스템에서의 SIP 기반의 확장된 Caller Preference 구현)

  • 조현규;장춘서
    • The Journal of the Korea Contents Association
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    • v.4 no.2
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    • pp.43-49
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    • 2004
  • SIP Caller Preference is an useful function that allows a caller to express preferences about request handling in servers. It can also feat appropriate call processing according to the callee capabilities. However, only the category of the media is considered as a criteria for target selection in the caller preference. In this case, if the callee's media information such as codec is different from the caller, an additional re­negotiation occurs for SIP call setup. Therefore, in this paper, we have suggested an extended caller preference to solve this problem. In our SIP based VoIP system, a network sewer uses detailed media informations for media stream in the session to select the target for SIP call setup. The sewer gives higher priority to the candidate which do not require re-negotiation for call setup, so that an effective call setup can be achieved in our system.

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Subjective Hand and Preference of Washed Fabrics according to Detergent of Drum Type Washer (드럼세탁기용 세제 특성에 따른 세탁포의 주관적 태평가 및 선호도에 관한 연구)

  • Ryu, Hyo-Seon;Roh, Eui-Kyung;Ju, Jeong-Ah;Oh, Young-Kee;Cho, Kee-Heon;Kwak, Sang-Woon
    • Journal of the Korean Society of Clothing and Textiles
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    • v.31 no.1 s.160
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    • pp.57-67
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    • 2007
  • The purpose of this study is to find out the better washing condition, especially on detergent contents to satisfy the consumer's concern on fabric hand using Drum Type Washer. The hand and preference of washed fabrics by various detergent contents were analyzed through subjective evaluation using questionnaire method in dry and wet state. Wine rank's semantic differential scale questions were developed with 27 kinds of adjective pairs and seven rank's scale questions were to evaluate preference of washed fabrics oil holistic touch, washing and rinsing effect and purchase intention of detergent. Group of trained panelists and untrained women panelists of $30{\sim}40$ years old were participated. The factors affecting consumer's taste for the washed fabrics were analyzed by SPSS 12.0. Smoothness showed relatively higher correlation with preference of washed fabrics on holistic touch, washing and rinsing effect and purchase intention of detergent. There were significant differences in preference of washed fabrics on holistic touch, washing and rinsing effect and purchase intention of detergent by detergent contents when tested in wet state. Fabrics washed with detergents of non-zeolite were appeared to be the preferred ones.

A Study on the Development and Consumer Preference of the Soup·Stew HMR New Products (탕·찌개류 HMR 신제품 개발을 위한 소비자 기호도 연구)

  • Lee, Seung-Min;Choi, Eun-Kyoung;Cho, Mi-Sook;Oh, Ji-Eun
    • The Journal of the Korea Contents Association
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    • v.19 no.8
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    • pp.123-136
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    • 2019
  • This paper is a study on the development and consumer preference of the soup stew HMR new products, and the main contents are as follows. A total of nine products were studied, including three developed products and six market products. For this study, the demographic characteristics, the awareness and attitude of HMR products were investigated. In addition, the consumer panel evaluated overall liking, appearance, color, flavor, and taste using the nine-point recertification scale, while the strength assessed viscosity, sweetness, saltiness, sourness, and Umami. Familiarity, health degree, Purchase intention and Recommendation intention were investigated and the reasons for preference and non preference were analyzed by multi-response method. The consumer preference analysis indicates that the product is competitive among existing products and that it would be desirable to improve after identifying the causes of non-preferred factors.

A Study on Personalized Recommendation Method Based on Contents Using Activity and Location Information (이용자 이용행위 및 콘텐츠 위치정보에 기반한 개인화 추천방법에 관한 연구)

  • Kim, Yong;Kim, Mun-Seok;Kim, Yoon-Beom;Park, Jae-Hong
    • Journal of the Korean Society for information Management
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    • v.26 no.1
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    • pp.81-105
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    • 2009
  • In this paper, we propose user contents using behavior and location information on contents on various channels, such as web, IPTV, for contents distribution. With methods to build user and contents profiles, contents using behavior as an implicit user feedback was applied into machine learning procedure for updating user profiles and contents preference. In machine learning procedure, contents-based and collaborative filtering methods were used to analyze user's contents preference. This study proposes contents location information on web sites for final recommendation contents as well. Finally, we refer to a generalized recommender system for personalization. With those methods, more effective and accurate recommendation service can be possible.

The Evaluation of Texture Image and Preference according to the Structural Characteristics of Silk Fabric (견직물의 구조적 특성에 따른 질감이미지와 선호도 평가)

  • Kim, Hee-Sook;Na, Mi-Hee
    • Korean Journal of Human Ecology
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    • v.18 no.1
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    • pp.137-143
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    • 2009
  • The purpose of this study is to examine the evaluation of texture image and preference according to the structural characteristics of silk fabric, and to analyze the effects of texture image and sensibility on the preference. 53 female subjects evaluated fabric image and sensibility of 17 specimens of white silk fabrics sold on the market with semantic differential scale. The data were analyzed through factor analysis, Pearson correlational coefficient and t-test using SPSS win 13.0. For the evaluation, structural characteristics such as fiber contents, weave type, weight and thickness were analyzed. Factor analysis showed that sensibilities were classified into 3 categories; 'surface property', 'weight', 'flexibility'. Fabric images were classified into 2 categories; 'elegance' and 'naturalness'. Statistically significant differences of structural characteristics on the texture image were observed. Weave type affected 'surface property' and fiber contents affected' flexibility'. Weight and weave type affected' elegance', too. The significant factors affecting preference were fabric image of 'elegance' and structural characteristics of 'weave type'. The results of this study showed that the most preferred silk fabric is smooth and soft satin weaved fabric with texture image of 'elegance'.

An Analysis on the Formative Requirements for Hybrid Characters and Influencing Relationship with Consumer Preference (하이브리드 캐릭터의 조형 요건과 소비자 선호도와의 영향관계 분석)

  • Kim, Jun-Su
    • Journal of Digital Contents Society
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    • v.19 no.7
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    • pp.1389-1395
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    • 2018
  • Hybrid is explained based on the logic of combination such as cross, melding, permeation, fusion, convergence etc. Such combination shows that it is more creative and effective in case of heterogeneity as compared to homogeneity and the same kind, and hybrid character has its meaning as a mean to produce a new creative image. In the context, this study aims to analyze influencing relationship through a practical analysis on how formative requirements for hybrid characters affects consumer preference. For the foregoing, this study conducted multiple regression analysis having familiarity, originality, meaningfulness, diversity as independent variables for formative requirements for characters, and consumer preference as a dependent variable. Analysis results show that familiarity, originality, diversity have a positive effect on consumers, whereas, meaningfulness has no significant impact on the consumer preference.

A Multimedia Contents Recommendation for Mobile Web Users

  • Kang, Mee;Cho, Yoon-Ho;Kim, Jae-Kyeong
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2004.11a
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    • pp.323-330
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    • 2004
  • As mobile market grows more and more fast, the mobile contents market, especially music contents for mobile phones have recorded remarkable growth. In spite of this rapid growth, mobile web users experience high levels of frustration to search the desired music. New musics are very profitable to the content providers, but the existing collaborative filtering (CF) system can't recommend them. To solve these problems, we propose an extended CF system to reflect the user's real preference by representing the characteristics of users and musics in the feature space. We represent the musics using the music contents based acoustic features in multi-dimensional feature space, and then select a neighborhood with the distance based function. Furthermore, this paper suggests a recommendation for procedure for new music by matching new music with other users' preference. The suggested procedure is explained step by step with an illustration example.

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Comparative Analysis of Online Real-time Lecture and On-demand Contents Lecture under the COVID-19 Situation in Korea

  • Nam, Sangzo
    • Journal of Advanced Information Technology and Convergence
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    • v.10 no.2
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    • pp.177-197
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    • 2020
  • Colleges have been forced to take non-face-to-face classes this year due to the COVID-19, and the situation is expected to continue unless the development of treatments and vaccines is carried out as soon as possible. In the situation where non-face-to-face classes are required under compulsion, two methodologies have been suggested as most representative alternatives to face-to-face classes: online real-time classes and on-demand contents classes. The purpose of this study is to compare the perceived convenience, self-fidelity, and preference of students between online real-time and on-demand contents classes by gender, school year grade, mostly using class media, and number of courses taken. Comparative results between online real-time and on-demand contents classes were statistically analyzed by surveying students at a university.

A Multimedia Contents Recommendation System using Preference Transition Probability (선호도 전이 확률을 이용한 멀티미디어 컨텐츠 추천 시스템)

  • Park, Sung-Joon;Kang, Sang-Gil;Kim, Young-Kuk
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.2
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    • pp.164-171
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    • 2006
  • Recently Digital multimedia broadcasting (DMB) has been available as a commercial service. The users sometimes have difficulty in finding their preferred multimedia contents and need to spend a lot of searching time finding them. They are even very likely to miss their preferred contents while searching for them. In order to solve the problem, we need a method for recommendation users preferred only minimum information. We propose an algorithm and a system for recommending users' preferred contents using preference transition probability from user's usage history. The system includes four agents: a client manager agent, a monitoring agent, a learning agent, and a recommendation agent. The client manager agent interacts and coordinates with the other modules, the monitoring agent gathers usage data for analyzing the user's preference of the contents, the learning agent cleans the gathered usage data and modeling with state transition matrix over time, and the recommendation agent recommends the user's preferred contents by analyzing the cleaned usage data. In the recommendation agent, we developed the recommendation algorithm using a user's preference transition probability for the contents. The prototype of the proposed system is designed and implemented on the WIPI(Wireless Internet Platform for Interoperability). The experimental results show that the recommendation algorithm using a user's preference transition probability can provide better performances than a conventional method.