• The Journal of the Korea Contents Association
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• v.12 no.6
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• pp.475-485
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• 2012

The purpose of this research study was to identify the factors that influence comsumer who make decisions on preferred coffee types. Data was collected for a month from September $12^{th}$ to October $10^{th}$, 2010 from 807 participants who visited a cafe' in Seoul. The Limdep(LIMited DEPendent) 8.0 program was used in analyzing the determinants for preferred types of coffee using the multinomial logit model(MNL) approach. The results revealed that there were four taste preference groups being Espresso, Americano, Cafe' Late, and Cafe' Mocha ; as well as confirming that demographic characteristics influenced the coffee selection attributes, type of packaging, preferred coffee brand, and visit frequencies. This study found seven coffee selection attributes were significant factors in influencing patrons choices for purchasing speciality coffee being age range, profession, packing status, elation, superficial appearance, weight control, and habitual, respectively. The research reflects the coffee selection attributes by the customers' preference and concludes that it would be helpful to make marketing strategy for particular coffee brands.

• Journal of the Korea Society of Computer and Information
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• v.17 no.8
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• pp.81-90
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• 2012

For digital TV, the recommendation of u-health personalized service of semantic environment should be done after evaluating individual physical condition, illness and health condition. The existing recommendation method of u-health personalized service of semantic environment had low user satisfaction because its recommendation was dependent on ontology for analyzing significance. We propose the personalized service recommendation method based on Naive Bayesian Classifier for u-health service of semantic environment in digital TV. In accordance with the proposed method, the condition data is inferred by using ontology, and the transaction is saved. By applying naive bayesian classifier that uses preference information, the service is provided after inferring based on user preference information and transaction formed from ontology. The service inferred based on naive bayesian classifier shows higher precision and recall ratio of the contents recommendation rather than the existing method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.49-65
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• 2023

In response to the growing global concern for the environment, the international community has recently committed to achieving 'carbon neutrality.' As a result, numerous studies have been conducted on mode choice models that include carbon emissions as a variable. However, few studies have established a correlation between individual preferences and carbon emissions. In this study, a new mode of transportation named sustainable public transit (SPT), incorporating carbon-reducing transport options like electric scooters, is proposed. Analyzing the individual preferences of commuters on carbon emissions through factor analysis, a stated preference (SP) survey was conducted. A mode choice model for SPT was constructed using multinomial logit models. The results of the analysis showed that gender, income, and specific preferences, such as a passion for exploring new routes, a preference for intermodal transfers, knowledge of carbon reduction, and carbon reduction practices, significantly influence latent preferences for SPT. Therefore, this study is significant as it considers carbon emissions as an attribute variable during the construction of mode choice models and reflects the individual preference variables associated with carbon reduction.

• Journal of the Korean Society for Railway
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• v.20 no.2
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• pp.288-298
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• 2017

The system of high-speed and conventional railway vehicles is diversified, and significant technological development in performance has been achieved. This study analyzed the modal change characteristics; furthermore, it estimated the value of travel time by improving the travel time and cost for the passenger's perception of railway. In this study, we formulate a mode choice model for passengers and compare it with the mixed logit model which reflects individual taste variation. In addition, the validity of the analysis is presented through an estimation the value of travel time using the derived model. For this purpose, a stated preference survey was conducted with 510 people using public transportation. The benefits of time-saving can be accurately determined by estimating the value of time spent on the railway. Appropriate fares for public transportation can also be estimated.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.672-677
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• 2006

유비쿼터스 컴퓨팅 환경에서 상황 인지 서비스 제공을 위한 프레임워크들은 환경에 있는 응용 서비스들로 하여금 사용자 행동 패턴을 지속적으로 모니터링하며, 하나의 중앙집중식 서버에서 축적된 사용자 프로파일을 관리하도록 개발되어 왔다. 그러나, 전체 환경이 사용자 개개인의 서비스에 대한 요구 및 선호도를 파악하고 관리하는 일은 비효율적이다. 그리하여, 사용자 프로파일 관리 서버를 사용하지 않고 개인화된 서비스를 제공하기 위하여 휴대용 정보 단말기가 직접 사용자의 서비스에 대한 선호도를 인식하고 관리하는 사용자 프로파일 관리 프레임워크를 제안한다. 스마트 홈 환경의 이동형 사용자의 컨텍스트 인식을 위해서는 사용자 몸에 부착되어 있는 센서들이 사용자에 대한 정보를 휴대용 정보 단말기로 전달하며, 각 정보 단말기는 다양한 센서들로부터 획득한 정보와 정보단말기를 통해 제공되는 사용자의 직접적인 요구정보를 서비스 목적에 맞게 재해석하여 사용자 선호도에 맞는 서비스 내용을 제공하도록 하는 것이다. 제안된 프레임워크는 휴대용 정보 단말기를 통해 사용자와 환경과의 상호작용을 필요로 하는 유비쿼터스 기술이 활용 가능한 다양한 어플리케이션에 광범위하게 활용될 수 있다. 더 나아가, 사용자의 사적인 정보 보호를 보장하면서 개인화된 서비스 제공을 가능하게 할 수 있다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.587-590
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• 2020

최근, 디지털 콘텐츠 산업이 폭발적으로 성장됨에 따라 고객 유치를 위한 개인화 추천 기술들이 많은 주목을 받고 있다. 개인화 추천 방식들을 큰 갈래로 나누어 본다면 협업 필터링 기술과 내용 기반 기술로 나눌 수 있다. 협업 필터링의 경우 개인화 추천에는 적합하지만 사용자 평가 데이터의 양이 방대해야 하며 초기에 평가자가 없는 콘텐츠에 대해 추천할 수 없는 초기 평가자 문제가 존재한다. 따라서 매일 방대한 양의 콘텐츠가 편입되는 분야에서 사용하기에 큰 결점이 될 수 있다. 본 논문에서는 영화들의 정보가 담긴 데이터 셋과 사용자 평가 데이터, 그리고 사용자의 선호 기준을 의미하는 메타 가중치를 활용한 내용 기반의 맞춤형 영화 추천 시스템을 제안한다. 논문에서는 먼저, 영화를 고를 때 일반적으로 중요시 보는 속성들을 활용하여 영화의 특징 벡터를 구성하고, 이를 사용자 평가와 결합하여 개인의 선호에 대한 특징 벡터를 구성하는 방법을 제안하며, 구성된 데이터와 코사인 유사도, 메타 가중치를 활용하여 사용자 선호와 유사한 영화들을 도출하는 방법을 제안한다. 또한, 평가데이터를 활용하여 구현된 추천시스템의 검증 프로세스를 구성하고, 검증 프로세스를 활용한 손실 함수를 설계하여 적합한 메타 가중치를 학습하는 방법을 제시한다. 본 논문에서 제안하는 시스템은 다수의 속성을 조합하여 활용하므로 추천 결과가 과도하게 특수화 되지 않을 수 있으며, 메타 가중치라는 요소를 통해 더욱 개인화 된 추천을 제공할 수 있다.

• The KIPS Transactions:PartA
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• v.10A no.3
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• pp.261-268
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• 2003

In this paper, we propose a new caching strategy for web servers. The proposed strategy collects only the statistics of the requested file, for example the popularity, when a request arrives. At a point of time, only files with higher forecasted popularity are cached all together. Forecasted popularity based lazy caching (FPLC) strategy uses exponential smoothing method for forecast popularity of web files. And, FPLC strategy shows that the cache hit ratio and the cache transfer ratio are better than those produced by other caching strategy. Furthermore, the experiment that is performed with real log files built from web servers shows our study on forecast method for popularity of web files improves cache efficiency.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.6
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• pp.63-74
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• 2005

In Electronic Commerce, the latest most of the personalized recommender systems have applied to the collaborative filtering technique. This method calculates the weight of similarity among users who have a similar preference degree in order to predict and recommend the item which hits to propensity of users. In this case, we commonly use Pearson Correlation Coefficient. However, this method is feasible to calculate a correlation if only there are the items that two users evaluated a preference degree in common. Accordingly, the accuracy of prediction falls. The weight of similarity can affect not only the case which predicts the item which hits to propensity of users, but also the performance of the personalized recommender system. In this study, we verify the improvement of the prediction accuracy through an experiment after observing the rule of the weight of similarity applying Vector similarity, Entropy, Inverse user frequency, and Default voting of Information Retrieval field. The result shows that the method combining the weight of similarity using the Entropy with Default voting got the most efficient performance.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.6
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• pp.894-902
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• 2016

The purpose of this study was to analyze the attributes considered as important by parents in the selection of laver for infants through conjoint analysis techniques. A total of 917 questionnaires were distributed in January 2016, of which 211 were completed (23.0%). Statistical data analyses were performed using SPSS/Win 21.0 for descriptive statistics and conjoint analysis. The conjoint design was applied to evaluate the hypothetical laver for infants. According to the analysis of attributes and levels of laver for infants, the relative importance of each attribute was follows: seasoning (26.55%), flavor (19.33%), texture (18.75%), oil (15.15%), size (10.61%), and certification (9.61%). The results of the conjoint analysis indicate that parents raising infants preferred laver with the characteristics of non-seasoning, general flavor, softness, half-size, organic certification, and perilla oil. The most preferred laver for infants gained a 53.7% potential market share from choice simulation compared with laver being sold. Using utility and relative importance, the laver market for infants was classified into two segments. As a result of market segmentation, parents of cluster 1 preferred the laver model being sold (soy seasoning) while parents of cluster 2 preferred the optimized laver model (non-seasoning).

• Korean Journal of Culture and Social Issue
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• v.26 no.3
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• pp.221-257
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• 2020

This study examined whether popular music lyrics, the new research topic, reflect changes in Koreans' cultural orientation and whether individuals' cultural orientation is related to the genre of popular music that they prefer. In Study 1, we content analyzed popular music lyrics from 1980 to 2018 to see if Koreans' cultural orientations changed over time. The analysis showed that as the release dates approached the 2010s, the lyrics expressed the ideal attitudes of individualist cultures more frequently than those of collectivist cultures; this suggests that Koreans have gradually become more individualistic over time. In Study 2, we examined the relationships between individuals' cultural orientations, preferences for various genres of popular music, and functions of music. The analysis showed that people with more collectivistic attitudes tended to prefer mid- and low-arousal music, such as Ballads and Rap/Hiphop, while those with less collectivistic attitudes preferred high-arousal music, such as Rock/Metal. This result is partly consistent with the hypothesis that collectivistic people would prefer lower to higher arousal music. In addition, our analysis showed the strongest positive relationship between collectivism and the social function of music; this result can be interpreted as indicating that collectivistic people use music to maintain good interpersonal relationships. This paper concludes by discussing the implications of these findings, the limitations of this study, and directions for further research.