• Title/Summary/Keyword: 선호속성

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Implicit Representation of Gender Stereotype: Priming Effects of Attribute Typicality and Gender Congruency (성별 고정관념의 암묵적 표상: 성별의 속성 전형성과 집단 일치성의 점화효과)

  • 이재호;방희정
    • Korean Journal of Cognitive Science
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    • v.14 no.2
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    • pp.37-46
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    • 2003
  • Two experiments were conducted to explore the implicit representation of gender-stereotype using primed naming task for prime-target pairs. In Experiment 1, Participants were presented gender's attributes as primes at SOA 250ms and were asked to pronounce person's names which differed in typicality and preference of gender's attributes. The results showed that gender congruent effects was not found, but typicality effects and interactions were found. In Experiment 2, Participants were presented gender's attributes as primes at SOA 250ms and were asked to pronounce gender's attributes which differed in typicality of gender's attributes. The results showed that woman's attributes superiority effects were found, but typicality effects were not. These results were discussed from a point of view of graded representation of gender stereotype and asymmetrical processing of gender stereotype to priming conditions in the implicit level.

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Modifying Sparse Data for Collaborative Filtering (협동적 여과를 위한 희소 데이터 변형 기법)

  • Kim, Hyung-Il;Kim, Jun-Tae
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.07b
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    • pp.610-612
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    • 2005
  • 협동적 여과를 이용한 추천 시스템은 데이터의 희소성 문제(sparseness problem)와 초기 추천 문제 (cold-start problem)에 대해 취약점을 가지고 있다. 협동적 여과를 이용한 추천 시스템에서 사용하는 선호도 데이터에 아이템들의 전체 수량에 비해 매우 적은 양의 아이템 선호도만 존재한다면 사용자들의 유사도 측정에 문제를 발생시켜 극단적인 경우엔 협동적 추천이 불가능할 경우가 발생한다. 이와 같은 문제는 선호도 데이터에 나타난 아이템들의 총수에 비해 사용자가 선호(구매)한 아이템이 극히 적은 수량으로 존재하기 때문이며 새로운 사용자의 경우에는 아이템 선호도 정보가 전혀 없기 때문에 유사 사용자를 추출하지 못하여 아이템을 전혀 추천할 수 없는 문제가 발생한다. 본 논문에서는 희소성이 높은 선호도 데이터를 희소하지 않은 상태로 변형하는 희소 데이터 변형 기법을 제안한다. 희소 데이터 변형 기법은 희소데이터에 나타난 사용자와 아이템의 추가 속성 정보의 확률분포를 이용하여 알려지지 않은 선호도 값을 예측함으로써 희소성이 높은 선호도 데이터를 변경하고, 변경된 선호도 데이터를 협동적 추천에 적용하여 추천 성능을 향상시킨다. 이와 같은 선호도 데이터 변경 기법을 데이터 블러링(data blurring)이라 한다. 몇가지 실험 결과를 통해 제안된 기법의 효과를 확인하였다.

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A Study on Consumer's Preference on Private Brand and National Brand by Characteristics (유통업체 브랜드(PB)와 제조업체 브랜드(NB) 상품의 속성별 소비자 선호 분석)

  • Hwang, Seong-Hyuk;Ku, Ja-Seong
    • Journal of Distribution Research
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    • v.13 no.4
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    • pp.47-70
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    • 2008
  • The purpose of this study is to find out characteristic of a product which has the most influence when consumer makes a purchase, and analyze if actual consumers make a purchase with recognition of the brand difference between PB and NB brands using conjoint analysis. As a result, the main factor which consumers consider when they purchase a product is the quality but the factor for brands (NB or PB) do not have an effect on their purchasing. The reason why consumers little consider a factor for PB or NB is that they do not have much knowledge of PB and they recognize the PB as a "me-too" product of NB. Therefore, retailers should develop more differentiated product in order to be recognized by consumers.

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The Comparative Analysis on the Change of People's Outdoor Space Preference according to Time Difference in Multi-Family Housing using a Conjoint Analysis (컨조인트 분석기법을 이용한 공동주택 옥외공간의 선호도 변화 비교 분석)

  • Hwang, Kyu-Sung;Lee, Chan-Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.11
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    • pp.4907-4913
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    • 2011
  • The purpose of this study is to find how the preferred properties of potential users for the outdoor space of the multi-family housing complex had changed according to time differance and to select the target market through market segmentation. The study has identified that the most important property among four properties had been changed from a Communication to a Amenity according to time difference. This is shown that considering information and communication as an important properties had been changed to regarding leisure and culture facilities as valuable properties.

Collaborative Filtering Method Using the Representative Attribute for Better Prediction Quality (향상된 예측을 위한 대표 속성을 이용한 협력적 여과 방법)

  • 류영석;양성봉
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.10b
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    • pp.33-35
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    • 2000
  • 사회의 복잡화와 인터넷의 성장으로 인하여 매일 급속도로 증가하고 있는 정보들을 사용자가 모두 검토해 보고 자신의 기호에 맞는 정보들만 선택하여 사용하기는 어려운 일이다. 이를 보완하기 위해 자동화된 정보 여과 기술이 사용되는데 대표적인 방법으로 내용 기반 여과(information Filtering) 기술과 협력적 여과(Collaborative Filtering) 기술이 있다. 이 중 협력적 여과 기술은 정보의 속성을 고려하지 않는다는 단점을 가지는데 본 논문에서는 이를 보완하여 정보의 대표 속성을 중심으로 선호도 예측을 수행하는 개선된 협력적 여과 방법을 제안한다. 그리고 기존 협력적 여과 기술과 예측의 정확성에 대하여 성능 비교 실험을 수행함으로써 제안한 방법의 타당성을 제시한다.

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Preferences of Foodservice Types for the Elderly Patients at the Long-term Care Facilities through Conjoint Analysis (컨조인트 분석에 의한 노인의료전문 병원의 급식서비스 선호도 연구)

  • Yoon, Hei-Ryoe;Cho, Mi-Sook
    • The Korean Journal of Food And Nutrition
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    • v.22 no.1
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    • pp.141-149
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    • 2009
  • The elderly population in Korea is growing rapidly and their needs for long-term care has also increased. By the year 2018, our society will be approaching aged society and by 2026 it will be a super-aged society. The purpose of this study was to employ conjoint analysis to establish the relative importance of foodservice encounters in terms of determining the utility values of hospital foodservice for elderly patients. According to the results pearson's R(0.420) and Kendall's tau(0.402) statistics showed that the model fits the data well(p<0.05). The relative importance scores of hospital foodservice encounters were as follows: dietary counseling with dietetics(51.2%), foodservice personnel(48.7%), and food(0.1%). A soft cooking method(0.001) was preferred to a general cooking method(0.001), and kind foodservice personnel(0.086) were preferred to quick service(-0.086). Finally, counseling with a dietitian once a week(-0.138) was preferred to counseling twice a week (-0.276). Based on this conjoint analysis, the most preferable model for foodservice at a long-term care facility would be; soft cooking methods, kind service by foodservice personnel, and dietetic counseling once a week. Overall, a better understanding of the specific needs of our institutionalized elderly is one of the key elements that can help our long-term care system develop improved foodservice programs.

Search for an Optimal-Path Considering Various Attributes (다양한 경로속성을 고려한 최적경로 탐색)

  • Hahn, Jin-Seok;Chon, Kyung-Soo
    • Journal of Korean Society of Transportation
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    • v.26 no.1
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    • pp.145-153
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    • 2008
  • Existing shortest-path algorithms mainly consider a single attribute. But traveler actually chooses a route considering not single attribute but various attributes which are synthesized travel time, route length, personal preference, etc. Therefore, to search the optimal path, these attributes are considered synthetically. In this study route searching algorithm which selects the maximum utility route using discrete choice model has developed in order to consider various attributes. Six elements which affect route choice are chosen for the route choice model and parameters of the models are estimated using survey data. A multinomial logit models are developed to design the function of route choice model. As a result, the model which has route length, delay time, the number of turning as parameter is selected based on the significance test. We use existing shortest path algorithm, which can reflect urban transportation network such as u-turn or p-turn, and apply it to the real network.

A Study on Individual User's Preference for Cloud Storage Service (클라우드 스토리지 서비스에 대한 개인 사용자의 선호 요인 연구)

  • Lee, Sewon;Hong, Ahreum;Hwang, Junseok
    • Journal of Technology Innovation
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    • v.23 no.1
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    • pp.1-36
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    • 2015
  • The purpose of this research is to find individual user's preference for cloud storage service such as Daum Cloud, Naver N-Drive, GoogleDrive, Dropbox, SkyDrive and iCloud. Through literature reviewed and pilot tests, 6 attributes of cloud storage service (storage capacity, perceived cost, collaboration, accessibility, social influence and perceived security) were selected and all 6 attributes had significant effects on the preference of cloud storage service by conjoint analysis. The results shows that the user's willingness to pay is estimated 10,553 won for the free storage, 4,646 won for the function for mobile accessibility, and 2,443 won for more reliable cloud computing service provider. This study has significance to apply conjoint analysis with economic, technological, and environmental factors to cloud storage service (SaaS) and shed light on policy promotion of next generation of cloud computing ecosystem by user perception with willingness to pay on the storage service.