• Proceedings of the Korea Information Processing Society Conference
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• 한국정보처리학회 2017년도 춘계학술발표대회
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• pp.708-711
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• 2017

최근 의류업계에서는 데이터마이닝을 이용하여 의상을 추천하는 시스템에 대한 연구가 활발하게 진행되고 있다. 하지만 기존 연구들은, 의상구매가 온 오프라인 모두에서 활발함에도 불구하고 온라인 쇼핑몰에서 얻을 수 있는 데이터에 국한되어 연구가 진행되고 있다. 본 논문에서는 온라인 데이터 위주의 기존 의상 추천 시스템을 스마트 홈 미러의 가상 착의시스템을 사용하여 온 오프라인 데이터를 모두 반영한 추천시스템을 구현했다. 또한 사용자에게 적합한 추천시스템을 제공하기 위해 지역별 인구분포와 사용자 기본DB를 단계별로 그룹화 했다. 정확도와 사용자 만족도를 향상 시키고자 단계별로 가중치를 부여해 협업 필터링과 날씨, 종류, 색상을 속성으로 한 내용기반 필터링을 결합하는 시스템을 제시했다.

• Proceedings of the Korea Information Processing Society Conference
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• 한국정보처리학회 2020년도 추계학술발표대회
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• pp.37-40
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• 2020

날씨에 대한 인류의 관심은 인류 역사가 시작되면서 지금까지 예측하며 관심 영역인 만큼 인류에게 끼치는 영향이 크다. 초기 인류에게 있어서 의류는 생존을 위한 생존 도구에서 현재는 패션의 영역으로 자기를 표출하거나 자신에게 가장 어울리는 옷을 찾기 위한 욕구로 발전해 왔다. 따라서 본 논문에서는 날씨에 따른 개인의 체감온도와 해당 날씨에 가장 선호하는 의상을 분석하고, 예측하며 추천해주는 시스템을 제안한다. 제안하는 시스템은 지속적인 유지 관리를 통해 보완해 나간다면 날씨와 패션 분야에서 다양한 접목을 하는 등 기술발전을 할 것으로 기대된다.

• Journal of the Korean Society of Clothing and Textiles
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• 제36권11호
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• pp.1222-1236
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• 2012

This study examined the effects of product recommendation services as an atmosphere for online mass customization shopping sites on consumers' cognitive and affective responses. We conducted a between-subject experimental study using a convenience sample of college students. A total of 196 participants provided usable responses for structural equation modeling analysis. The findings of the study support the S-O-R model for a product recommendation system as an element of the shopping environment with an influence on OMC product evaluations and arousal. The results showed that OMC product recommendation service positively affected cognitive and affective responses. The findings of the study suggest that OMC retailers might pay attention to the affective and cognitive responses of consumers through product recommendation services that can enhance product evaluations and OMC usage intentions.

• Proceedings of the Korean Society of Computer Information Conference
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• 한국컴퓨터정보학회 2023년도 제68차 하계학술대회논문집 31권2호
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• pp.445-446
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• 2023

본 논문에서는 봇 프레임워크 기반의 날씨 기반 코디 챗봇을 설계하고 구현한다. 이 챗봇은 셀레니움을 이용한 크롤링을 통하여 현재 위치의 날씨 정보와 원하는 지역의 날씨 정보를 제공한다. 또한 현재 위치의 날씨에 맞는 의류를 추천한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제41권7호
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• pp.768-774
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• 2016

This paper deals with a method to recommend the combination of items as a group according to similarity to handle application area such as fashion and cooking, while the previous methods recommend single item such as a book, music or movie. Collaborative filtering is a method to recommend an item selected by users with similar tendency based on similarity between users. In this paper, the proposed method generates a set of frequent items based on collaborative filtering and association rules and recommends a group by similarity between groups. To show the validity of the proposed method, experiments are performed with purchase data collected from e-commerce for four months.

• Fashion & Textile Research Journal
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• 제23권2호
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• pp.200-211
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• 2021

This study examines the effects of fashion influencers' body types (realistic versus ideal body types) on self-expression, self-representation, and recommendation intentions, as mediated by familiarity toward influencers. Although fashion influencers lead to a positive consumer response compared to traditional advertisements, previous research on the effects of fashion influencers on consumers is limited. Thus, this study tests the role of consumers' socio-psychological aspects in understanding how and why fashion influencers affect consumers' behavioral intentions associated with self-expression, self-representation, and influencer recommendation. A total of 180 women in their 20s and 30s participated in the survey. The responses were collected after showing them stimuli featuring fashion influencers with either ideal or realistic body shapes. The data were analyzed using SPSS18.0 for descriptive statistics, and AMOS 18.0 for confirmatory factor analysis and structural equation modeling. The results showed that participants who were shown realistic body types perceived familiarity, which generated positive effects on self-expression, self-representation, and recommendation intentions. Hence, the effects of influencers' body types on recommendation intention are mediated by familiarity. Self-expression and self-representation intentions also increase influencer recommendation intention. Comparatively, participants who were shown ideal body types only induced higher self-representation intention, which increased their recommendation intention. The current findings can help fashion marketers select the appropriate influencers who fit their target customers as promotional models, as well as to induce changes in consumers' behavioral intention.

• Journal of the Korean Society of Clothing and Textiles
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• 제47권4호
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• pp.711-728
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• 2023

This study aims to validate the user experience associated with the personalized recommendation systems of fashion vertical platforms. The investigation focused on women aged 18 to 30 with prior experience using personalized fashion recommendation systems. The collected data were analyzed using SPSS 26.0 and AMOS 26.0, and the outcomes can be summarized as follows. Firstly, the diversity and usefulness of information quality exerted a positive effect on use satisfaction. Secondly, the affirmative impact of the reliability of system quality on user satisfaction was established, although stability was not confirmed. Thirdly, the study identified a favorable connection between ease-of-use of service quality and user satisfaction, while the influence of tangibles was unsubstantiated. Fourthly, the degree of self-reference was found to have a positive effect on user satisfaction. Fifthly, a constructive relationship emerged between user satisfaction and both continuous-use intention and recommendation intention. Lastly, there was a significant difference in the magnitude of the effect of ease-of-use on satisfaction according to self-regulatory focus. The findings of this study hold the potential to enhance the explanatory and predictive power of the field of consumer behavior within the novel shopping landscape of fashion vertical platforms.

• Journal of the Korean Society of Clothing and Textiles
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• 제35권8호
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• pp.890-905
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• 2011

This study investigated service quality perception, purchase satisfaction, recommendation intention, and switching intention of fashion consumers according to the types of internet shopping malls. The survey was conducted from February 7 to 21 in 2011, and 294 responses were used in the data analysis. The statistical analysis methods were frequency analysis, factor analysis, reliability analysis, ANOVA, and regression analysis. The result of the service quality perception of internet fashion consumers was classified by site characteristics, reliability, enjoyment, product diversity, responsibility, security, and order convenience. There were significant differences in the site characteristics, reliability, enjoyment, responsibility, and security of service quality perception by the types of internet shopping malls. In addition, the factors of service quality perception that could affect the purchase satisfaction of fashion consumers showed differently according to the types of internet shopping malls. The purchase satisfaction of fashion consumers influenced the recommendation intention in all types of internet shopping malls and the purchase satisfaction influenced the switching intention in fashion specialized internet shopping malls.

• Journal of Korea Multimedia Society
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• 제13권3호
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• pp.467-474
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• 2010

The market of Internet-based fashion/coordination shopping malls have been growing rapidly year by year. In accordance with this growth, Internet fashion shopping malls are also making a lot of efforts to increase their revenue by displaying new fashion products on a high spot or by having professional models wear them to make them more attractive to the customers. If online shopping malls have the functionality of automatically calculating the matching degree of lower and upper clothes, it could play a role of off-line shop assistants and provide a more convenient way of purchasing fashion products for customers. In this paper, we present a learning system adopting the content-based filtering method for online shopping malls, which automatically calculates the matching degree of lower and upper clothes and recommends the most well-matched pair.

• Fashion & Textile Research Journal
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• 제17권2호
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• pp.216-226
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• 2015

This study identifies factors of perceived risk of up-cycling fashion products and investigates perceived risk factors that influence consumers' trust, purchase intention, and recommendation intention towards upcycling fashion products. We also examine the relationship of trust, purchase intention, and recommendation intention for upcycling fashion products. A qualitative research method using a free narrative form and depth interview were used. The perceived risk from up-cycling fashion products generated 5 factor solutions: aesthetic risk, sanitary risk, social risk, performance risk, and economic risk. Next, 201 effective data were collected from a questionnaire survey and analyzed with SPSS 22.0. The results are summarized as follows. First, aesthetic risk and performance risk had a negative effect on products. Second, aesthetic risk and performance risk had negative influence on purchase intention for upcycling fashion products. Third, performance risk had a negative impact on recommendation intention for upcycling fashion products. Fourth, trust had positive effect on purchase intention and recommendation intention for upcycling fashion products. The results of the current study provides various theoretical and practical implications for marketers and retailers interested in up-cycling fashion products.