• Journal of Intelligence and Information Systems
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• v.13 no.4
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• pp.65-78
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• 2007

This paper proposes a new method of weighted template matching for machine-printed numeral recognition. The proposed weighted template matching, which emphasizes the feature of a pattern using adaptive Hamming distance on local feature areas, improves the recognition rate while template matching processes an input image as one global feature. Template matching is vulnerable to random noises that generate ragged outlines of a pattern when it is binarized. This paper offers a method of chain code trimming in order to remove ragged outlines. The method corrects specific chain codes within the chain codes of the inner and the outer contour of a pattern. The experiment compares confusion matrices of both the template matching and the proposed weighted template matching with chain code trimming. The result shows that the proposed method improves fairly the recognition rate of the machine-printed numerals.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.12
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• pp.1709-1715
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• 2002

신사복 정장은 일상의 관습으로 착용되는 가장 중요한 항목으로서, 사무직, 관리 직, 전문직 등의 정신노동자들에 게 폭넓게 수용되는 매우 중요한 의복항목이 다. 따라서 소비자의 감성에 부합되는 신사복 개발을 위해 신사복 디자인에 대한 감성연구가 필요하다. 이에 본 연구에서는 신사복 상의 디자인 개발을 위해서 소비자의 감성에 적합한 신사복 상의를 적절하게 표현해 줄 수 있는 감성 어휘를 추출하고 그 인자를 분석하였다. 요인분석 결과,7개 의 요인과 67개 의 감성 어휘 가 채택되었다. 선택된 감성어휘는 인자별로 대별하여 7개의 요인으로 묶어서 대표적인 요인명을 붙인 결과, 요인 1은 품위성 요인. 요인 2는 매력성 요인. 요인 3은 실용성 요인, 요인 4는 체형성 요인. 요인 5는 외관성 요인. 요인 6은 남성미 요인. 요인 7은 활동성 요인이라고 하였다.

• Proceedings of the ESK Conference
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• 1996.04a
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• pp.136-140
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• 1996

제품개발의 개념이 기능이나 성능중심에서 인간의 감성중심으로전환되고 있다. 그러나 인간의 감 성은 정성적 언어로 표현되며 이것을 물리적 디자인요소로 전환하는 것이 필요하다. 이를 위하여는 우선적으로 인간의 감성을 정량화하는 것이 선결되어야한다. 따라서 본 연구의 목적은 다변량해석기법 을 활용하여 고객의 제품에 대한 정성적 이미지를 정량적 데이터로 변환하여 이를 감성 데이터베이스로 구축하는데 있다. 감성 데이터베이스는 감성어휘와 이의 제품에 대한 정량적 수치 데이터로 구성되고, 이를 위해서는 감성어휘 선정, 디자인 요소에 의한 제품의 분류, 감성어휘와 디자인요소간의 상관도 도출 등이 필요하다. 감성어휘는 요인분석에 의해 선정하고, 제품은 아이템/카테고리에 의해 분류하며, 감성어휘와 디자인요소간의 상관성에 대해서는 다변량해석기법 특히, 수량화이론 1류를 사용해서 정량화 한다. 이렇게 구축된 감성 데이터베이스는 감성공학적 디자인 요소변환 지원시스템의 감성데이터 처리 서브시스템의 핵심 역활을 한다.

• Knowledge Management Research
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• v.21 no.3
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• pp.27-44
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• 2020

In order to solve the user's information overload problem, recommender systems infer users' preferences and suggest items that match them. The collaborative filtering (CF), the most successful recommendation algorithm, has been improving performance until recently and applied to various business domains. Visual information, such as book covers, could influence consumers' purchase decision making. However, CF-based recommender systems have rarely considered for visual information. In this study, we propose VizNCS, a CF-based deep learning model that uses visual information as additional information. VizNCS consists of two phases. In the first phase, we build convolutional neural networks (CNN) to extract visual features from image data. In the second phase, we supply the visual features to the NCF model that is known to easy to extend to other information among the deep learning-based recommendation systems. As the results of the performance comparison experiments, VizNCS showed higher performance than the vanilla NCF. We also conducted an additional experiment to see if the visual information affects differently depending on the product category. The result enables us to identify which categories were affected and which were not. We expect VizNCS to improve the recommender system performance and expand the recommender system's data source to visual information.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.1
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• pp.1-6
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• 2013

Variety of smart devices including smart phone have become and essential item in user's daily life. This means that smart devices are good mediators to get collecting user's behavior by sensors mounted on the devices. The information from smart devices is important clues to identify by analyzing the user's preferences and needs. Through this, the intelligent service which is fitted to the user is possible. This paper propose a smart service recommendation model based on user scenario using fusion context-awareness. The information for recommendation services is collected to make the scenario depending on time, location, action based on the Fusion process. The scenarios can help predict a user's situation and provide the services in advance. Also, content categories as well as the content types are determined depending on the scenario. The scenario is a method for providing the best service as well as a basis for the user's situation. Using this method, proposing a smart service model with the fusion context-awareness based on the hybrid sensing is the goal of this paper.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.373-380
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• 2017

We propose the SoMA(System of Making Avatars) based on a commercial 3D game engine. It first decomposes a given character into assemblable pieces, then gives the user them as prefab components so that he or she can reassemble and/or customize them to be plenty of characters. To accomplish this, it implements the character assembly structure as an hierarchy, the upper levels of which are categorized for gross assembly, and the lower levels of which are parameterized for detailed customization. It also defines a hierarchical naming convention for ease of access to the structure. Finally, it provides body, clothes, and attachment systems to make relevant characters.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.445-456
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• 2021

The purpose of this study is to identify the importance of variables affecting women's golf wear sales with macroeconomic variables and consumer selling prices that affect consumers' purchasing behavior, and to propose a price strategy to increase sales of golf wear. Data of domestic women's golf wear brands were analyzed using decision tree algorithms and ensemble. Consumer selling price is the most significant factors in terms of sales volume for T-shirt, pants and knit, while categories were found to be the most important factors in addition to consumer sales prices for skirt and one piece dress. These findings suggest that items have different economic variables that affect consumers' purchasing behavior, suggesting that sales and profits can be maximized through appropriate price strategies.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.87-107
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• 2016

Understanding market convergence has became essential for small and mid-size enterprises. Identifying convergence items among heterogeneous markets could lead to product innovation and successful market introduction. Previous researches have two limitations. First, traditional researches focusing on patent databases are suitable for detecting technology convergence, however, they have failed to recognize market demands. Second, most researches concentrate on identifying the relationship between existing products or technology. This study presents a platform to identify the opportunity of market convergence by using product databases from a global B2B marketplace. We also attempt to identify convergence opportunity in different industries by applying Structural Hole theory. This paper shows the mechanisms for market convergence: attributes extraction of products and services using text mining and association analysis among attributes, and network analysis based on structural hole. In order to discover market demand, we analyzed 240,002 e-catalog from January 2013 to July 2016.