• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.5
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• pp.129-136
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• 2003

A representative payment broker system is SET and one of its signature shcemes is a dual digital signature scheme. A dual digital signature scheme expose neither user's payment information(credit card number etc.) to merchandiser, nor user's order information to bank So it keeps user's Privacy safe. The digital signature scheme like this is being necessary as E-commerce is revitalized. But a dual digital signature of SET is not appropriate for wireless environments because it needs so many computations and communications. In this paper, we propose a signcryption scheme that generates a polynomial using a payment information for merchandiser and an order information for bank in order to reduce communications. We analyze the problem of existing signcryption schemes and dual digital signature schemes. Also we analyze the security properties of the proposed scheme.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.467-477
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• 2004

While recommender systems were used by a few E-commerce sites former days, they are now becoming serious business tools that are re-shaping the world of I-commerce. And collaborative filtering has been a very successful recommendation technique in both research and practice. But there are two problems in personalized recommender systems, it is First-Rating problem and Sparsity problem. In this paper, we solve these problems using the associative relation clustering and “Lift” of association rules. We produce “Lift” between items using user's rating data. And we apply Threshold by -cut to the association between items. To make an efficiency of associative relation cluster higher, we use not only the existing Hypergraph Clique Clustering algorithm but also the suggested Split Cluster method. If the cluster is completed, we calculate a similarity iten in each inner cluster. And the index is saved in the database for the fast access. We apply the creating index to predict the preference for new items. To estimate the Performance, the suggested method is compared with existing collaborative filtering techniques. As a result, the proposed method is efficient for improving the accuracy of prediction through solving problems of existing collaborative filtering techniques.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.109-125
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• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.853-862
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• 2003

Many more use e-mail purely on a personal basis and the pool of e-mail users is growing daily. Also, the amount of mails, which are transmitted in electronic commerce, is getting more and more. Because of its convenience, a mass of spam mails is flooding everyday. And yet automated techniques for learning to filter e-mail have yet to significantly affect the e-mail market. This paper suggests Web Mail Filtering Agent for Personalized Classification, which automatically manages mails adjusting to the user. It is based on web mail, which can be logged in any time, any place and has no limitation in any system. In case new mails are received, it first makes some personal rules in use of the result of observation ; and based on the personal rules, it automatically classifies the mails into categories according to the contents of mails and saves the classified mails in the relevant folders or deletes the unnecessary mails and spam mails. And, we applied Bayesian Algorithm using Dynamic Threshold for our system's accuracy.

• Archives of design research
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• v.16 no.2
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• pp.161-170
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• 2003

This study aims to understanding the effects of culture on websites with emphasis on the website structure and navigation. The website is inherently‘cultural’because anyone around the world can access to website if he or she is equipped with appropriate equipment. For the importance of cultural role in website, various researches have been conducted to understand the relationship between culture and website. However they tended to focus mainly on phenomenal matters such as color, layout, icon etc. There have been not so many thorough attempts to causal relationships between website and‘thick culture’in depth. The study conducted cross-cultural usability testing of websites between Korea and America. At first, representative I-commerce websites of Korea and America were selected and they were analyzed by the selected frameworks such as layout, display type, element type, and the relationship with homepage and sub-page navigation. The results were used to construct typical prototypes of website for Korea and America for experiment. Two websites were used for cross-cultural usability testing though specially-developed remote testing. 20 users from each country participated in the usability testing. The result shows that Korean users peformed better usability testing for Korean style structure of website while American counterparts showed better performances in American style of websites. Other various significant findings were revealed.

• Journal of the Korea Society of Computer and Information
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• v.8 no.4
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• pp.92-103
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• 2003

Great many advertisements are serviced in on-line by development of electronic commerce and internet user's rapid increase recently. However, this advertisement service is stopping in one-side service of relevant advertisement rather than doing users' inclination analysis to basis. Therefore, want advertisement service that many websites are personalized for efficient service of relevant advertisement and service through relevant server's log analysis research and enforce. Take advantage of log data of local system that this treatise is not analysis of server log data and analyze user's Preference degree and inclination. Also, try to propose advertisement system personalized by making relevant site tributary category and give weight of relevant tributary. User's preference user preference which analysis is one part of cooperation fielder ring of web personalized techniques use information in visit site tributary and suppose internet user's action in visit number of times of relevant site and try inclination analysis of mixing form. Express user's preference degree by vector, and inclination analysis result uninterrupted data that simplicity application form is not regarded and techniques that propose inclination analysis change of data since with move data use and analyze newly and proposed so that can do continuous renewal and application as feedback Sikkim. Presented method that can choose advertisements of relevant tributary through this result and provide personalized advertisement service by applying process such as user inclination analysis in advertisement chosen.

• The KIPS Transactions:PartD
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• v.13D no.5 s.108
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• pp.661-670
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• 2006

With the development of e-Commerce and the proliferation of easily accessible information, information filtering systems such as recommender and SDI systems have become popular to prune large information spaces so that users are directed toward those items that best meet their needs and preferences. Until now, many information filtering methods have been proposed to support filtering systems. XML is emerging as a new standard for information. Recently, filtering systems need new approaches in dealing with XML documents. So, in this paper our system suggests a method to create multiform user profiles with XML's ability to represent structure. This system consists of two parts; one is an administrator profile definition part that an administrator defines to analyze users purchase pattern before a transaction such as purchase happens directly. an other is a user profile creation part module which is applied by the defined profile. Administrator profiles are made from DTD information and it is supposed to point the specific part of a document conforming to the DTD. Proposed system builds user's profile more accurately to get adaptability for user's behavior of buying and provide useful product information without inefficient searching based on such user's profile.

• Asia pacific journal of information systems
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• v.20 no.4
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• pp.125-147
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• 2010

This paper Introduces an electronic auction service to be provided on Interactive TV (T-auction). This converged service is expected to much enhance the quality of the service to current online auction users through vivid visualization and live Interactive experience. Our study focuses on how the characteristics of the interactive TV-based shopping platform can affect users' attitudes towards the converged service. To develop our proposed research model, we extended the technology acceptance model and integrated it with a hedonic factor, or perceived enjoyment to reflect the dual characteristics of the converged system. We also adopted the variable of intermediary trust In the service as a critical mediating determinant for a successful commutations-mediated commerce. The research model was verified with an empirical study conducted on 970 Korean online auction users. Results show that both trust and perceived usefulness positively affect user adoption of the service. Trust had not only a direct effect on users' attitudes toward T-auction but also an indirect one by mediating the service quality, information quality, perceived enjoyment and ease of use. Meanwhile, the hedonic factor of T-auction contributes to increasing both the level of the intermediary's trust and its perceived usefulness. Users' enjoyment also was found to help form a positive attitude toward T-auction services. Theoretical and practical implications of this study for current e-auction service providers and potential t-auction service providers are also discussed.

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.1-15
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• 2006

Currently the mobile web service is growing with a tremendous speed and mobile contents are spreading extensively. However, it is hard to search what the user wants because of some limitations of cellular phones. And the music is the most popular content, but many users experience frustrations to search their desired music. To solve these problems, this research proposes a hybrid recommendation system, MOBICORS-music (MOBIle COntents Recommender System for Music). Basically it follows the procedure of Collaborative Filtering (CF) system, but it uses Contents-Based (CB) data representation for neighborhood formation and recommendation of new music. Based on this data representation, MOBICORS-music solves the new item ramp-up problem and results better performance than existing CF systems. The procedure of MOBICORS-music is explained step by step with an illustrative example.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6B
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• pp.908-920
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• 2010

In recent years, mobile phone market is saturated in number of user term. Associated service providers struggle to provide various mobile services such as Internet, e-commerce, game, music etc. to increase ARPU (average revenue per user) instead. In this study we explore the factors which affect price tabs of mobile communication. As a conceptual foundation, this study introduces user factors-users' propensity to use mobile phones-as independent variables and mobile service functions as mediating variables. The research model was phones-as independent variables and mobile service functions as mediating variables. The research model was tested with data from Web-based survey of 1,500 mobile users and analyzed by structural equation modeling (SEM). Our results suggest that user factors impact the usage of mobile service functions and mobile service functions for information and convenience are positively related to price tabs of mobile communication. Implications for mobile service providers and policy makers are discussed.