• Journal of Fashion Business
• /
• v.27 no.3
• /
• pp.50-62
• /
• 2023

The e-commerce fashion market has experienced a remarkable growth, leading to an overwhelming availability of shared information and numerous choices for users. In light of this, chatbots have emerged as a promising technological solution to enhance personalized services in this context. This study aimed to develop user-product attributes for a chatbot-based personalized fashion recommendation service using big data text mining techniques. To accomplish this, over one million consumer reviews from Coupang, an e-commerce platform, were collected and analyzed using frequency analyses to identify the upper-level attributes of users and products. Attribute terms were then assigned to each user-product attribute, including user body shape (body proportion, BMI), user needs (functional, expressive, aesthetic), user TPO (time, place, occasion), product design elements (fit, color, material, detail), product size (label, measurement), and product care (laundry, maintenance). The classification of user-product attributes was found to be applicable to the knowledge graph of the Conversational Path Reasoning model. A testing environment was established to evaluate the usefulness of attributes based on real e-commerce users and purchased product information. This study is significant in proposing a new research methodology in the field of Fashion Informatics for constructing the knowledge base of a chatbot based on text mining analysis. The proposed research methodology is expected to enhance fashion technology and improve personalized fashion recommendation service and user experience with a chatbot in the e-commerce market.

• Journal of Fashion Business
• /
• v.17 no.5
• /
• pp.101-119
• /
• 2013

The purpose of this study is to consider the interactivity which appeared on the fashion media that focus on Showstudio's fashion projects. Showstudio is a famous fashion site that was founded by the famous photographer, Nick Knight, which has displayed interactive projects with fashion designers and artists. The methods of this study are undertaken by theoretical studies and project analysis. The 38 projects under the 'interactive' category are being chosen among archive data and the project explanations, photos and videos provided from the site are studied. Interactivity of fashion projects in Showstudio is considered by main factors such as two-way communication, participation, user control, and responsiveness. Two-way communication appears as transactional communication in the creation process and feedbacks from contents of users. The characteristic of participation appears as participation in the creation process and the practical use of contents. User control appears as control of contents, user interface and streaming media systems. The characteristic of responsiveness appears as real time and synesthesia responsiveness between the user and contents. Showstudio show free communication through digital information transmit system and also indicate the opportunity of innovative interactions among users, media, and contents.

• Journal of Fashion Business
• /
• v.26 no.1
• /
• pp.1-15
• /
• 2022

Digital transformation has induced changes in human life patterns; consumption patterns are also changing to digitalization. Entering the era of industry 4.0 with the 4th industrial revolution, it is important to pay attention to a new paradigm in the fashion industry, the shift from developer-centered to user-centered in the era of the 3rd industrial revolution. The meaning of storing users' changing life and consumption patterns and analyzing stored big data are linked to consumer sentiment. It is more valuable to read emotions, then develop and distribute products based on them, rather than developer-centered processes that previously started in the fashion market. An AI(Artificial Intelligence) deep learning algorithm that analyzes user emotion big data from user experience(UX) to emotion and uses the analyzed data as a source has become possible. By combining AI technology, the fashion industry can develop various new products and technologies that meet the functional and emotional aspects required by consumers and expect a sustainable user experience structure. This study analyzes clear and useful user experience in the fashion industry to derive the characteristics of AI algorithms that combine emotions and technologies reflecting users' needs and proposes methods that can be used in the fashion industry. The purpose of the study is to utilize information analysis using big data and AI algorithms so that structures that can interact with users and developers can lead to a sustainable ecosystem. Ultimately, it is meaningful to identify the direction of the optimized fashion industry through user experienced emotional fashion technology algorithms.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.14 no.1
• /
• pp.173-198
• /
• 2003

The purpose of this study is to provide suggestions for the design of fashion fields’ websites that can help users conduct their researches. The evaluation criteria were developed and the usability tests of websites in fashion fields were conducted by user groups. In addition, the questionnaires were distributed to user groups in fashion fields to collect data associated with users' information needs and their information use behaviors. Following an analysis, a model of the effective websites design in fashion fields is provided.

• Journal of Korea Multimedia Society
• /
• v.17 no.11
• /
• pp.1374-1381
• /
• 2014

Digital technology With the popularization of computers and IT technology development is causing a dramatic change across the human life. Increase of profit in fashion industry has a significant impact on the overall industry. It has been studied to develop consumer oriented higher value-added fashion products of including clothes using digital technology abroad. In this paper, we propose a system that when user stand in front of display, user can show body captured depth camera look the coordination of a variety of costume and fashion concept through a magic mirror. Using the system, we will satisfy the convenience of user and be used as a way appropriate to clothing shopping in the shortest time. The system will develop personalized fashion content industry enhanced interaction.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.6
• /
• pp.207-212
• /
• 2007

Recently, requriements that people want to receive various information related with fashion are increasing. A lot of internet shopping malls and corporations provide information about fashion. However, those systems do not give enough information about fashion. To solve these problems, the paper provides the recommend technique for providing complex fashion information on mobile devices. The providing system implements fasion ontology by using XML. The XML ontology has dewey number as an attribute. The recommend technique uses this number and find LCA(Lowest Common Ancestor) on the fashion ontology. Then those child nodes under the LCA are recommended as related information. The results are displayed on the mobile browser. The system provides function for taking a picture or movie of fashion contents. Those movies and pictures are UCC(User Created Content)s. The system is a novel system that can recommend complex fasion information on mobile devices.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.36 no.1
• /
• pp.36-45
• /
• 2012

This study locates factors that affect the intention to use fashion SNS (social network service) and intention for word-of-mouth on fashion SNS. Independent variables were fashion shopping orientation, attitude toward innovative products, fashion leadership, and demographics. A questionnaire method was used to collect data on college students while factor analyses, multiple regression, $x^2$ analyses, and Pearson correlation coefficients were applied in analyzing data. Factor analyses resulted in four factors for fashion shopping orientation, three on attitude toward innovative products and two on fashion leadership. Multiple regression analyses showed that information compatibility of attitude toward innovative products had a significant impact on two models of intention to use fashion SNS and two models of intention for word-of-mouth on fashion SNS. Opinion leadership and gender were significant factors for two models of intention to use fashion SNS, which means that women are likely to have more intention to use fashion SNS. Meanwhile, fashion innovativeness was found to be a significant factor on two models of intention for word-of-mouth on fashion SNS. Shopping orientation factors were not important for any model. $x^2$ analyses showed that women rather than men wanted more information on online fashion shows, general fashion information, and user participation programs. Fashion major students wanted more information on online fashion shows and user participation programs than non-fashion major students.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.8 no.4
• /
• pp.270-275
• /
• 2008

Under ubiquitous environment, recommendation system is using the collaborative filtering methods by quantifying context information, but insufficient context information can cause inaccurate recommendation result. In order to solve such problems, the researcher used context information and user's profile. But service history information in users' profiles can have the problems of being influenced by change of the user's taste or fashion as time passes by. In addition, context information and user's profile can't be properly inter-locked according to situation, which can cause inaccurate predictability. In this paper, in case a user's taste or fashion is changed as time passes by, the researcher didn't apply bundled-up value to the user's profile but applied different weight according to change of time. And the researcher could solve the problem that context information and a user's profile can't be properly inter-locked according to situation by applying different weight to the result gained by means of collaborative filtering and then by unifying it. In such ways, the researcher could improve predictability.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.47 no.4
• /
• pp.711-728
• /
• 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.

• Fashion & Textile Research Journal
• /
• v.12 no.1
• /
• pp.68-79
• /
• 2010

This study was fulfilled in the purpose of proposing construction strategies of fashion information industry through the analysis of information user's satisfaction/dissatisfaction on information quality. The research was performed through a depth interview. Data were collected from 18 fashion information users(designers and merchandisers) who were working at fashion apparel industry during October to November 2007. Results from the study showed that there were three dimensions and 18 components of satisfaction/dissatisfaction on fashion information quality: Information quality(understandability, value-added, level of detail, relevance, diversity, objectivity, completeness, accuracy, quantitativeness), Service quality(responsiveness, accessibility, cost efficiency, empathy, reliability), System quality(currency, ease of use, format, timeliness). And the information users were perceiving that there were some changes in notion of preferring information, searching for information and usage of information.