• Journal of Korea Society of Industrial Information Systems
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• v.10 no.3
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• pp.1-6
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• 2005

This study tried to identify factors influencing on customer's trust in Mobile Commerce Sites. Four factors were found ; transaction security, site image, navigation usability, payment convenience. These factors showed strong correlations with customer's trust. Implications of the study and further research issues are discussed.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.172-177
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• 2006

본 논문은 모바일커머스 사이트의 신뢰도에 영향을 미치는 요인들을 거래안전성, 사이트이미지, 검색기능성, 그리고 결제편의성으로 분류하여 관련 연구들을 통해 검증된 요인들을 추출하였다. 그리고 모바일커머스 사이트에서 이용 경험이 있는 고객들을 대상으로 직접 설문조사를 통해 사이트의 신뢰도 형성에 영향을 미치는 요인들을 식별해내고 구매의도에 어떠한 영향을 미치는 지를 분석한 결과를 바탕으로 고객과의 신뢰에 기반한 모바일커머스의 실제적인 활성화에 기여하고자 한다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.611-620
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• 2018

With the revitalization of alley market area becoming a major goal of the urban regeneration project, an understanding on customer characteristics that affect the sales of alley market areas is needed. As spatial heterogeneity appears to exist in alley market areas, the use of GWR (Geographically Weighted Regression) is required as an alternative to OLS (Ordinary Least Squares) regression. This study analyzes effects of customer characteristics on sales of 1007 alley market areas in Seoul. Comparing R squared and AICc, results show that GWR is better than OLS regression. According to OLS regression, the ratio of female, the ratio of 40's and 50's, the number of employees, the opening rate of establishment, the density of building and the size of alley market area have positive effects on sales, while the ratio of 20's and 30's, the distance of bus stop and that of subway station have negative effects. As a result of comparing local regression coefficients of geographically weighted regression analysis, the ratio of female customers has the greatest effect on the northwestern region, followed by the southwestern region, the central region and the northeastern region. The ratio of 20's and 30's and that of 40's and 50's effect on the southeastern and northeastern regions, and then the southwestern region. It is expected that this study will help to identify marketing target for each alley market area.

• 정보화사회
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• s.177
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• pp.38-39
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• 2005

(주)배리스(VARIS. 대표 이광민)는 2005년 1월 18일 법인을 설립한 신생벤처이다. ' VAluable Relationship Information System' 약자로 회사 명칭을 정한 데서도 '관계'를 중요시 하는 이 업체의 설립취지를 엿볼 수 있다. 이 업체의 창업 아이템인 '휴대전화번호 e메일 서비스' 역시 이 연장선에 있다. 휴대전화번호를 e메일 식별자로 하자는 역발상은 제법 신선하다. 또 병행 개발중인 '고객맞춤형 택시콜 서비스' 역시 사업체와 이용자간 '최적화된' 편리를 도모하기 위한 데서 착안된 서비스이다.

• 정보보호뉴스
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• s.137
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• pp.42-45
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• 2009

지난해 옥션, SK브로드밴드, GS칼텍스 등의 고객정보 유출사건이 반복적으로 발생하면서 집단소송제 제기 등 개인정보보호의 문제는 사회적인 분쟁으로 확산되고 있는 실정이다. 이런 상황에서 정부의 안일한 대응과 체계적이지 못한 시스템 미비 등이 문제의 근원으로 지적되고 있다. 하지만 보다 근본적인 원인은 바로 턱없이 부족한 개인정보보호의 예산과 실효성 없는 대책에 있다. 따라서 일련의 사건들이 재발되지 않고 개인정보 유출이라는 불법행위가 근절되기 위해서는 개인정보보호 예산 편성 강화와 인터넷상 주민번호를 대체할 식별번호(i-PIN)의 도입을 통한 제도적, 기술적 보완을 강구해야 한다. 특히 정보통신 시설 및 개인정보 보호에 관한 법제를 정비하는 것이 시급하다.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.79-98
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• 2011

This paper proposes a semantic recommendation technique for a personalized e-commerce portal. Semantic recommendation is achieved by utilizing the attributes of products. The semantic similarity of the products is merged with the rating information of the products to provide an accurate recommendation. The recommendation technique also analyzes various attitudes of the customer to evaluate the implicit rating of products. Attitudes are classifies into three types such as "purchasing product", "adding product to shopping cart", and "viewing the product information." We implicitly track customer attitude to estimate the rating of products for recommending products. Also we implement a session validation process to identify the valid sessions that are highly important for giving an accurate recommendation. Our recommendation technique shows a high degree of accuracy as we use age groupings of customers with similar preferences. The experimental section shows that our proposed recommendation method outperforms well known collaborative filtering methods not only for the existing customer, but also for the new user with no previous purchase record.

• The Transactions of the Korea Information Processing Society
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• v.7 no.1
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• pp.146-155
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• 2000

This paper describes a 4-state bar code called HANGUL 4 ST that has been specifically designed for automatic processing of the letter mails, A HANGUL 4 ST bar code is a necessary data base that is applied data capture and data carrier with it all the information necessary for sorting, the amount capture for transportation of mail items, and valued-added services such as indicia, tracking and trace. The 4-state bar code information contents are composed of a postal code, delivery point, customer information including customer identification number and name, and parity bits for error detect and correct. The data density capability of HANGUL 4 St allows all useful sorting data and customer data to be encoded on one label. This supports better automatic processing in mail items, higher level of customer service and more efficient operation.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.325-345
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• 2023

In the rapidly evolving domain of e-commerce, our study presents a cohesive approach to enhance customer satisfaction prediction from online reviews, aligning methodological innovation with practical insights. We integrate the RFE-SHAP feature selection with LDA topic modeling to streamline predictive analytics in e-commerce. This integration facilitates the identification of key features-specifically, narrowing down from an initial set of 28 to an optimal subset of 14 features for the Random Forest algorithm. Our approach strategically mitigates the common issue of overfitting in models with an excess of features, leading to an improved accuracy rate of 84% in our Random Forest model. Central to our analysis is the understanding that certain aspects in review content, such as quality, fit, and durability, play a pivotal role in influencing customer satisfaction, especially in the clothing sector. We delve into explaining how each of these selected features impacts customer satisfaction, providing a comprehensive view of the elements most appreciated by customers. Our research makes significant contributions in two key areas. First, it enhances predictive modeling within the realm of e-commerce analytics by introducing a streamlined, feature-centric approach. This refinement in methodology not only bolsters the accuracy of customer satisfaction predictions but also sets a new standard for handling feature selection in predictive models. Second, the study provides actionable insights for e-commerce platforms, especially those in the clothing sector. By highlighting which aspects of customer reviews-like quality, fit, and durability-most influence satisfaction, we offer a strategic direction for businesses to tailor their products and services.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.12 no.1
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• pp.55-66
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• 2002

Electronic cash system based on anonymous coins have been invented by David Chaum. However, von Solms and Naccache discovered that such anonymous coins also very well suited to support criminals in Blacoailing. In this paper, we suggest a method that a client informs a bank of the information about blackmailing attack by using Schnorr identification protocol of XTR version at the stage of identification, whenever he is blackmailed. In general, blackmailing is the most serious among the various drawbacks of electronic cash system. Especially, blackmiling to be done when the client is kidnapped brings a fatal result to electronic cash system. But if the Schnorr identification protocol of XTR version is used, we can efficiently defeat blackmailing without assumption required in the existing method to defeat blackmailing.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.191-203
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• 2022

In this paper, we developed a system that intelligently identifies skin image data from big data collected from social media Instagram and extracts standardized skin sample data for skin condition diagnosis and management. The system proposed in this paper consists of big data collection and analysis stage, skin image analysis stage, training data preparation stage, artificial neural network training stage, and skin image identification stage. In the big data collection and analysis stage, big data is collected from Instagram and image information for skin condition diagnosis and management is stored as an analysis result. In the skin image analysis stage, the evaluation and analysis results of the skin image are obtained using a traditional image processing technique. In the training data preparation stage, the training data were prepared by extracting the skin sample data from the skin image analysis result. And in the artificial neural network training stage, an artificial neural network AnnSampleSkin that intelligently predicts the skin image type using this training data was built up, and the model was completed through training. In the skin image identification step, skin samples are extracted from images collected from social media, and the image type prediction results of the trained artificial neural network AnnSampleSkin are integrated to intelligently identify the final skin image type. The skin image identification method proposed in this paper shows explain high skin image identification accuracy of about 92% or more, and can provide standardized skin sample image big data. The extracted skin sample set is expected to be used as standardized skin image data that is very efficient and useful for diagnosing and managing skin conditions.