• Journal of Korea Multimedia Society
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• v.5 no.6
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• pp.712-729
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• 2002

In this study, we evaluated degree of importance of e-marketplace solution selection factors. Factor analysis was conducted to find out relationships among various variables which come from literature survey. The result shows that 16(sixteen) -selection variables regarding solution characteristics could be grouped into four areas 'flexibility', 'ease of use', 'security', and 'economy'. And 11(eleven) selection variables regarding to vendor characteristics could be grouped into three areas, 'vendor's support', vendor's general situation', and 'vendor's business accomplishment`. Through various analysis, we found important factors for 3 types of operational companies, buyer-biased, seller biased and neutral. 'Security for data item' was showed as the most important factor for all kind of B2B operational companies. For buyer-biased companies, additional supporting manpower, solution education, and educational cost are shown to be more important factors than others. Place of education, education hours and education level are important for 'Neutral' companies. And the factor 'market share of vendor' are important for 'seller biased' companies.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.6
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• pp.367-378
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• 2006

A mobile phone has became as a payment tool in e-commerce and on-line banking areas. This trend of a payment system using various types of mobile devices is rapidly growing, especially in the Internet transaction and small-money payment. Hence, there will be a need to define its standard for secure and safe payment technology. In this thesis, we consider the service types of the current mobile payments and the authentication method, investigate the disadvantages, problems and their solutions for smart and secure payment. Also, we propose a novel authentication method which is easily adopted without modification and addition of the existed mobile hardware platform. Also, we present a simple implementation as a demonstration version. Based on virtual machine (VM) approach, the proposed model is to use a pseudo-random number which is confirmed by the VM in a user's mobile phone and then is sent to the authentication site. This is more secure and safe rather than use of a random number received by the previous SMS. For this payment operation, a user should register the serial number at the first step after downloading the VM software, by which can prevent the illegal payment use by a mobile copy-phone. Compared with the previous SMS approach, the proposed method can reduce the amount of packet size to 30% as well as the time. Therefore, the VM-based method is superior to the previous approaches in the viewpoint of security, packet size and transaction time.

• The Journal of Society for e-Business Studies
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• v.9 no.3
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• pp.155-167
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• 2004

At this time, the two main techniques for achieving web personalization assistant systems generally concern direct manipulation and software agents. While both direct manipulation and software agents are intended for permitting user to complete tasks rapidly, efficiently, and easily, their methodologies are different. The central debate involving these web personalization techniques originates from the amount of control that each allows to, or holds back from, the users. Direct manipulation can provide users with comprehensibel, predictable and controllable user interfaces that give them a feeling of accomplishnent and responsibility. On the other hand, the intelligent software components, the agents, can assist users with artificial intelligence by monitoring or retrieving personal histories or behaviors. In this empirical study, two web personalization assistant systems are evaluated. One of them, WebPersonalizer, is an agent based user personalization tool; the other, AntWorld, is a collaborative recommendation tool which provides direct manipulation interfaces. Through this empirical study, we have focused on two different paradigms as web personalization assistant systems : direct manipulation and software agents. Each approach has its own advantages and disadvantages. We also provide the experimental result that is worth referring for developers of electronic commerce system and suggest the methodologies for conveniently retrieving necessary information based on their personal needs.

• Information Systems Review
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• v.7 no.1
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• pp.97-113
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• 2005

This paper designed and implemented(programmed) a comparative shopping agent that helps consumers to shop at on-line shopping malls over Internet. At offline stores, as consumers usually tell a sales clerk about a manufacturer, functions and price range of an item they want to purchase, the sales clerk will show the products or relevant catalogues. Then the consumer will compare functions, design and prices of the product and buy it with the lowest price. PriceMeter, a comparative shopping agent, introduced in this paper, is designed best geared to this consumers' buying behavior. Basically, as consumers enter a manufacturer's name, price, features and etc. at a search window, PriceMeter will search the web and provide a list of product informations such as features and prices that meet the search conditions. Consumers can see the information in either a form of catalogue or a printing format. As consumers click specific items to examine closely, it will show prices and information about shopping malls that sell the requested items. Clicking a 'Buy' icon, the consumers will be transferred to the right web page at the linked shopping mall. The emergence of the comparative shopping agent will expedite a consumer-centered retailing economy in the age of e-commerce. As consumers are provided with a better set of product and shopping mall information, they can make better purchasing decisions and gain more bargaining power shifted from manufacturers(sellers). The presentation of this comparative shopping agent is intended to promote the consumer-centered B2C e-commerce.

• The Journal of Society for e-Business Studies
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• v.23 no.1
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• pp.65-88
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• 2018

This case is an analysis of how a late comer to the market of online dating in Korea, Dorsia, successfully develops its services called Amanda. Since 2010, the online dating market in Korea has been fast growing. Despite its short history, many corporations have attempted to make success in the market. But most of them were unable to gain foothold in a market where the first comer had a huge advantage. Amanda, however, has provided differentiated services to great success in a short period. This paper conducted a semi-structured interview with major executives of Dorsia to acquire data which were then used to interpret based on the theories of business management and psychology. This study presents a strategic insight into how competitiveness can be gained in internet-based businesses in the online dating market, as well as those in markets that have similar traits. Moreover, by identifying issues that need to be addressed in order for Amanda to continue its growth, the study seeks to simultaneously review the issues that need resolution related to online commerce, as well as the great potential of online commerce.

• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.389-390
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• 2002

It is important that acquire information about if customer has some habit in electronic commerce application of internet base that led in recommendation service for customer in dynamic web contents supply. Collaborative filtering that has been used as a standard approach to Web personalization can not get rapidly user's preference change due to static user profiles and has shortcomings such as reliance on user ratings, lack of scalability, and poor performance in the high-dimensional data. In order to overcome this drawbacks, Web usage mining has been prevalent. Web usage mining is a technique that discovers patterns from We usage data logged to server. Specially. a technique that discovers Web usage patterns and clusters patterns is used. However, the discovery of patterns using Afriori algorithm creates many useless patterns. In this paper, the enhanced method for the construction of dynamic user profiles using validated Web usage patterns is proposed. First, to discover patterns Apriori is used and in order to create clusters for user profiles, ARHP algorithm is chosen. Before creating clusters using discovered patterns, validation that removes useless patterns by Dempster-Shafer theory is performed. And user profiles are created dynamically based on current user sessions for Web personalization.

• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.633-642
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• 2006

In the Internet environment many interactions between many users and unknown users take place and it is usually rare to have the trust information about others. Due to the lack of trust information, entities have to take some risks in transactions with others. In this perspective, it is crucial for the entities to be equipped with functionality to accumulate and manage the trust information on other entities in order to reduce risks and uncertainty in their transactions. This paper is concerned with a quantitative computational trust model which takes into account multiple evaluation criteria and uses the recommendation from others in order to get the trust for an entity. In the proposed trust model, the trust for an entity is defined as the expectation for the entity to yield satisfactory outcomes in the given situation. Once an interaction has been made with an entity, it is assumed that outcomes are observed with respect to evaluation criteria. When the trust information is needed, the satisfaction degree, which is the probability to generate satisfactory outcomes for each evaluation criterion, is computed based on the empirical outcome outcome distributions and the entity's preference degrees on the outcomes. Then, the satisfaction degrees for evaluation criteria are aggregated into a trust value. At that time, the reputation information is also incorporated into the trust value. This paper also shows that the model could help the entities effectively choose other entities for transactions with some experiments in e-commerce.

• Journal of the Korea Society of Computer and Information
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• v.19 no.6
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• pp.129-138
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• 2014

The Electronic contract means creation sign management and storage of contract by online without limitations of the time and space through the electronic signature and encode which based on the Certificate instead of the past that treatment the contract such as creation sign management and storage of contract by face-to-face. Recently, the remarkable development of information and communication technology with supplying the high-speed Internet services. Accordingly, the transaction contract made by these also, the steady legal effect occurred by two or more parties by legal action which is the electronic agreement of expression. and it makes agreement improving corporate productivity and it can control the whole process such as contract documents and the actual buying store provision. Like this it has many benefits so, it suddenly rising as the new axis of economic activity area, it is a reality. In this change of era, with the establishment of electronic contracts, there are many problems are occurred to the expression of parties which is core of the contract on civil code so, the systematic legal composition is required. Thus, in this study will propose the reasonable improvements about the issue of electronic contract through the consideration.

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.193-200
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• 2014

Due to the advent of ubiquitous computing environment, it is becoming a part of our common life style. And tremendous information is cumulated rapidly. In these trends, it is becoming a very important technology to find out exact information in a large data to present users. Collaborative filtering is the method based on other users' preferences, can not only reflect exact attributes of user but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. In this paper, we propose clustering method by user's features based on SOM for predicting purchase pattern in u-Commerce. it is necessary for us to make the cluster with similarity by user's features to be able to reflect attributes of the customer information in order to find the items with same propensity in the cluster rapidly. The proposed makes the task of clustering to apply the variable of featured vector for the user's information and RFM factors based on purchase history data. To verify improved performance of proposing system, we make experiments with dataset collected in a cosmetic internet shopping mall.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.163-172
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• 2012

Collaborative filtering which is used explicit method in a existing recommedation system, can not only reflect exact attributes of item but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. This paper proposes the personalized recommendation system using RFM method and k-means clustering in u-commerce which is required by real time accessablity and agility. In this paper, using a implicit method which is is not used complicated query processing of the request and the response for rating, it is necessary for us to keep the analysis of RFM method and k-means clustering to be able to reflect attributes of the item in order to find the items with high purchasablity. The proposed makes the task of clustering to apply the variable of featured vector for the customer's information and calculating of the preference by each item category based on purchase history data, is able to recommend the items with efficiency. To estimate the performance, the proposed system is compared with existing system. As a result, it can be improved and evaluated according to the criteria of logicality through the experiment with dataset, collected in a cosmetic internet shopping mall.