• Journal of the Korea Society of Computer and Information
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• v.25 no.1
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• pp.131-140
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• 2020

In this study, we analyzed the effect of consumer's cognitive response, emotional response and behavioral response on online shopping stockouts (ISRI: Individual Stockout Response Index). And we try to show the heterogeneity of the degree of consumer response by subdivision market based on the regularity of distribution. The ISRI was developed by Kim and Lee in 2016 and 2018, which were based on the items and factors of cognitive, emotional and behavioral responses. The exponential stockouts response of consumers in this study will give an accurate picture of what consumers want when stockouts. further research should be done on how consumers' reactions are influenced by situational characteristics, consumer characteristics, store characteristics and brand / product characteristics. Especially, the price level of the product will affect the consumer 's response in the case of online fashion goods shopping.

• The Journal of Society for e-Business Studies
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• v.19 no.4
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• pp.21-30
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• 2014

Personalized data of users at social network service can be used as a new resource for providing personalized nutrition information. Although providing personalized information for nutrition using social data, there are a few studies on providing personalized nutrition information with customized user preference based on social network service. The purpose of this study is to implement the clustering of data analysis with collected personal data of Facebook users. To find out the method for providing personalized information, this study described an effective method for providing nutrition information by analyzing web posting on Facebook that can be called a typical social network service. According to the result from clustering, sodium and sugars were important variables from diet of user. Furthermore, the importance of elements of user's diet has some differences according to vendor/manufactures.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.7
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• pp.738-742
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• 2008

The user model is an indispensable factor for providing users with personalized. services in the ubiquitous computing environment. In general user models, services which users prefer should be described in advance so that the system can recognize and interpret them automatically. Also, user's preferences as to the change of situation are not reflected in general user models due to their ignoring the situation. In this paper, we propose the self-growing user model which learns user experience and the system which automatically provides personalized community services through extracting user preferring services by situation.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06a
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• pp.125-127
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• 2012

IT기술의 발달과 함께 학습자의 학습 성향, 능력, 환경 등을 인지하고 그에 적절한 서비스가 가능한 지능형 교육 시스템이 많은 관심을 받고 있다. 학습자에게 지능적이고 개인화된 서비스를 위해서는 학습자를 인지하기 위한 작업이 선행되어야 하며, 이 인지과정을 위해서는 학습자의 학습 과정에서 발생한 데이터를 수집하고 분석하게 된다. 하지만, 수집된 데이터가 학습자의 일관되지 못한 행위나 예측하지 못한 학습 성향을 포함하고 있다면, 그 결과를 신뢰하기 어렵다. 본 논문에서는 학습자에게서 수집된 데이터를 SVDD를 이용하여 가중치를 부여하고, 그 값을 인지과정에 활용한다. 실험에서는 홈 인테리어 교육 컨텐츠 기반에 학습자의 학습 행위에 대한 학습 성향을 진단하기 위해 DOLLS-HI를 이용하였고, 수집된 학습자의 데이터를 분석하여 전통적인 분석 방법 대비 제안하는 방법의 유효함을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.509-512
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• 2013

최근 모바일 기기의 고도화 및 위성 기술의 발달에 따라, 모바일 단말에서 개인 위치의 수집이 용이해지고 있고, 이에 따라 개인 위치 정보 기반의 다양한 서비스들이 주목 받고 있다. 수집된 위치 정보를 필요한 기준에 따라 적절하게 분석한다면 다양한 위치기반 서비스 및 개인용 스마트 기기 인터페이스 등을 위한 매우 유용한 정보로 활용 할 수 있다. 예를 들어 각 지역별 유동인구 또는 사람들이 밀집한 특정 지역이나, 시간대를 확인 하여 위치기반 서비스의 성능을 향상 시킬 수 있다. 또한 스마트 기기에서 사용자의 위치와 연관된 이동 방식을 인지하여 개인 사용자에게 필요한 인터페이스를 제공할 수 있다. 이 논문에서는 위치 정보 수집을 위한 툴에 대할 설명과, 약 1개월간 수집된 위치정보를 기반으로 분석 결과를 소개한다. 이 결과를 토대로 이동 방식 인식을 위한 알고리즘 개발 시 필요한 점들을 고찰한다.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.343-351
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• 2020

The present study investigated the related variables of cognitive function, subjective cognitive decline and cognitive training effects. The cognitive training was composed of mete-cognitive education and cognitive task performing. Twenty older adults attended for 14 weeks and were tested before and after the training. Results show that their cognitive level was related with age, self-esteem and personality traits. And subjective cognitive decline was related depression, anxiety, personality traits, self-efficacy, self-esteem and subjective age, but it does not reflect objective cognitive impairments. Their cognitive test scores were enhanced after training in MMSE, memory and executive function, and enhanced scores were related with age, subjective cognitive decline, anxiety, self-efficacy, self-esteem, subjective age and personality traits. Findings suggest one's personality and psychological state need to be considered for the effects of cognitive training.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.409-415
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• 2009

The head-related transfer function (HRTF), which has an important role in virtual sound localization has different characteristics across the subjects. Measuring HRTF is very time-consuming and requires a set of specific apparatus. Accordingly, HRTF customization is often employed. In this paper, we propose a method to search an adequate HRTF from a set of the HRTFs. To achieve rapid and reliable customization of HRTF, all HRTFs in the database are partitioned, where a binary search tree was employed. The distortion measurement adopted in HRTF partitioning was determined in a heuristic way, which predicts the differences in perceived sound location well. The DC-Davis CIPIC HRTF database set was used to evaluate the effectiveness of the proposed method. In the listening test, where 10 subjects were participated, the stimuli filtered by the HRTF obtained by the proposed method were closer to those by the personalized HRTF in terms of sound localization. Moreover, performance of the proposed method was shown to be superior to the previous customization method, where the HRFT is selected by using anthropometric data.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.164-175
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• 2022

The OTT (Over The Top) platform promotes itself as a distinctive competitive advantage in that it allows users to stay on the platform longer and visit more often through a Personalized Recommendation Service. In this study, the characteristics of the Personalized Recommendation Service are divided into three categories: recommendation accuracy, recommendation diversity, and recommendation novelty. Then proposed a research model which affects the usefulness of users to recognize recommendation services by each characteristics and leads to satisfaction of expectations. The result of conducting an online survey of 300 people in their 20s and 30s who subscribe Netflix shows that the perceived usefulness increased when the accuracy, variety, and novelty of Netflix's Recommendation Service were high. It was also confirmed that high perceived usefulness leads to satisfaction of expectations before and after Netflix use. The derived research results can confirm the importance of evaluating the personalized recommendation service in terms of user experience and provide implications for ways to improve the quality of recommendation services.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.35 no.2
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• pp.109-133
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• 2024

This study investigated the impact of the technical characteristics of Generative AI (GAI) and librarians' personal traits on their intention to use GAI. Personalization, interaction, and context awareness were considered as technical characteristics of GAI that influence the intention to use GAI, while innovativeness and frequency of GAI use were considered as librarians' personal traits. The study targeted 187 librarians working in libraries, and 165 questionnaires were collected and analyzed. The results showed that the technical characteristics of GAI had a statistically significant impact on the intention to use GAI. Additionally, librarians' personal traits, namely innovativeness and frequency of GAI use, were also found to have a significant impact on the intention to use GAI. The findings of this study can be used as valuable information to help librarians increase their intention to use GAI and improve the quality and satisfaction of library services.

• 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.