• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.454-456
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• 2001

일반적으로 확률에 기반한 연산자를 사용하는 진회연산(EC)은 전역 탐색에는 효율적이나 국소 탐색에는 그렇지 못하다. 이러한 문제점은 대화형 진회연산(IEC)에서 더욱 심각해지는데, 이는 개체들을 사용자가 직접 평가하는데 따른 세대 길이의 제한이 있기 때문이다. 본 논문에서는 HCI 분야에서 잘 알려져 있는 직접조작 방법(Direct Manipulation : DM)을 적용하여 이것을 해결하는 방법을 제안한다. 각각의 개체들에 대한 인터페이스 진화 연산자를 사용하는 대신 지적조작을 사용함으로써 사용자는 개체의 진화에 직접 개입할 수 있고, 이를 통해 진화연산자를 사용하는 전역 탐색 능력은 그래도 유지한 채 대화형 진화연산의 단점을 극복할 수 있다. 이러한 직접조작 개념을 대화형GA에 기반한 패션 디자인 시스템에 적용하였고 이러한 응용이 효과적이었음을 실험을 통해 보였다.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.138-147
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• 2022

Recently, chatbots have been applied in various fields and have shown good results, and many attempts to use chatbots in shopping mall product recommendation services are being conducted on e-commerce platforms. In this paper, for a conversation system that recommends a fashion that a user wants based on conversation between the user and the system and fashion image information, a transformer model that is currently performing well in various AI fields such as natural language processing, voice recognition, and image recognition. We propose a multimodal-based improved transformer model that is improved to increase the accuracy of recommendation by using dialogue (text) and fashion (image) information together for data preprocessing and data representation. We also propose a method to improve accuracy through data improvement by analyzing the data. The proposed system has a recommendation accuracy score of 0.6563 WKT (Weighted Kendall's tau), which significantly improved the existing system's 0.3372 WKT by 0.3191 WKT or more.

• Smart Media Journal
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• v.10 no.1
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• pp.116-123
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• 2021

Due to the rapid growth of the online fashion market and the resulting expansion of online choices, there is a problem that the seller cannot directly respond to a large number of consumers individually, although consumers are increasingly demanding for more personalized recommendation services. Images are being tagged as a way to meet consumer's personalization needs, but when people tagging, tagging is very subjective for each person, and artificial intelligence tagging has very limited words and does not meet the needs of users. To solve this problem, we designed an algorithm that recognizes the shape, attribute, and emotional information of the product included in the image with AI, and codes this information to represent all the information that the image has with a combination of codes. Through this algorithm, it became possible by acquiring a variety of information possessed by the image in real time, such as the sensibility of the fashion image and the TPO information expressed by the fashion image, which was not possible until now. Based on this information, it is possible to go beyond the stage of analyzing the tastes of consumers and make hyper-personalized clothing recommendations that combine the tastes of consumers with information about trends and TPOs.

• Journal of Fashion Business
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• v.16 no.2
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• pp.27-43
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• 2012

Considering the rapid growth of mobile industry and the emerging application marketing, this study focused on fashion applications, which had not drawn much academic attention before, and analysed relevant content composition, information-seeking benefits based on users' lifestyles and resulting differences in satisfaction and loyalty. In short, fashion applications were divided into fashion and non-fashion brand apps. Brand apps were subdivided into luxury, women's wear, men's wear, casual wear, sportswear, accessories and the like. Non-brand apps included commerce, magazine, information, style tip, SNS and wardrobe manager types. As for users' lifestyle-based information search, the higher the tendency to search information on the internet and to favour reasonable consumption, the more basic information on products and brands they sought, whereas the higher the tendency to look for high-profile brands and to favour global culture, the more additional information like images or entertainments they sought. To sum up, given that studies on fashion-specific applications were rare, the present study reviewed and categorized current fashion applications, and suggested theoretical and practical groundwork for developing content based on target consumers' lifestyle and for planning fashion applications in practice.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.459-463
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• 2006

사회가 개인화하고 사용자의 요구가 다양해짐에 따라, 사용자의 감성을 기반으로 하여 서비스를 제공하는 많은 연구와 응용 어플리케이션을 개발되고 있다. 그 중, 시각적인 정보에 대한 인간의 감성은 디자인, 패션, 상품개발과 같은 여러 분야에서 그 중요성이 부각되어 다각적인 측면으로 많은 연구가 진행되고 있다. 그러나, 그러한 연구들이 아직 괄목할 만한 성과를 내지 못하고 있다. 더욱이, 시각 정보로부터 유용한 요소를 추출하고, 감성을 예측하는 자동화된 시스템이 매우 미흡한 실정이다. 그러므로, 본 연구는 칼라와 텍스처를 자동으로 추출하고 그와 관련된 특정 감성에 대해 효율적으로 예측 가능한 직물감성 예측 신경망 시스템을 개발하였다. 또한 칼라와 텍스처와 같은 시각정보와 감성과의 관계를 규명하고자 각 시각 특징을 입력 값으로 하고, 감성 값을 출력 값으로 하는 신경망을 개발하였고 실험을 통해 각 감성에 따라 칼라와 텍스처 요소가 다르게 영향을 미친다는 사실을 증명할 수 있었다.

• Journal of the Korea Society of Computer and Information
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• v.9 no.1
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• pp.45-54
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• 2004

A CAD and diagraming program of clothing and fashion design field within the country variously exist, but this paper implements design CAD and diagraming system based on diagraming piece with database system. Proposal system can be used quickly and easily to designer because of providing various diagraming piece. intend to utilize the data to diagraming piece provide with various classification and key word. 2D fashion design system provide GUI, various drawing tool, vector type document. application data based on XML, diverse library and easy mapping capacity for user.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.198-206
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• 2008

The fashion in the virtual world is emerging as a new genre. Gammer in virtual community shares the avatars and space for their activities and for flourishing their virtual lives, they start to demand indispensable daily items. The gammer's demands lead to the concept of second life in the virtual world which was introduced in 2003. The trading business system is realized at the virtual world with various daily items, developed by individual programmers, through the virtual money, which may converted into real money. Particularly, fashion industry's inherent nature of snagging on-line trading is no more, now, set to ready in the virtual world let alone various daily virtual items developed by individual programmers. The purpose of this study is, focused on the virtual second life, to introduce the model of fashion business in virtual world and overall informations regarding second life business systems so as to provide the fundamental data for opening the web.3.0 era. Further various fashion items in the virtual world, developed by individual programers, will be another boost for shaping another virtual fashion business genre.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.686-687
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• 2022

Existing clothing product search is possible only with text search, so it is not possible to properly search for the product that the user is looking for, and it takes a lot of time to search for the desired product. In addition, it was difficult to know where to sell unbranded products such as Soho Mall products, and it was difficult to search for detailed attributes of fashion products. To solve this problem, we would like to propose a deep learning technique that can search for the exact information that the user wants through the learned image search.

• Journal of Internet Computing and Services
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• v.9 no.5
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• pp.99-108
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• 2008

This paper proposes an image retrieval system which integrates metadata, contents, and emotions in textile images. First, the proposed system searches images using metadata. Among searched images, the system retrieves similar images based on color histogram, color sketch, and emotion histogram. To extract emotion features, this paper uses emotion colors which was proposed on 160 emotion words by H. Nagumo. To enhance the user's convenience, the proposed textile image retrieval system provides additional functions as like enlarging an image, viewing color histogram, viewing color sketch, and viewing repeated patterns.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.465-469
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• 2007

본 논문에서는 텍스타일 영상의 내용 데이터와 메타데이터를 결합시킨 영상 검색 시스템을 제안한다. 섬유 패션의 정보를 가지고 있는 메타데이터와의 결합은 그 동안의 섬유 패션 산업과 관련된 영상 검색 시스템에서 진보된 것이다. 우선 메타데이터의 정보를 통해서 영상을 검색하게 된다. 검색된 영상 안에서 색상히스토그램과 색상스케치를 통하여 주어진 영상과 비슷한 영상들을 검색하게 된다. 이러한 방법은 영상내용만을 통해 검색했던 것 뿐만아니라 텍스트가 가지고 있는 의미를 보안하여 보다 효과적인 검색을 할 수 있었다. 본 논문에서 제안된 시스템에서 부가적인 기능인 돋보기 기능, 색상 히스토그램 기능, 색상 스케치 기능, 반복 패턴 보기 기능을 통해 검색된 영상들의 정보를 효과적으로 제공함으로써 사용자의 편의를 강화하였다.