• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.5
• /
• pp.1-7
• /
• 2020

We can build regular customer relationships combining SNS (social networking service) with shopping mall like offline trade. A customer who once purchased is registered as reaular and the relationship continues afterward. The registered regular customer get sthe information about objective product shipment and besides it, he contacts with a story of frams, growth of vegetables, sows to harvests. Consumer can purchase with one click necessary foods as he looks at timeline. Sellers give information about news. discounts to customers. Besides it, food storages, recipes can be given to consumers. The good point here is that selling and promoting can be performed within one account. This is better than link is provided for selling an promoting separately. Like this, besides personal connections using SNS, categorization function gives consumers on line shopping mall service. Once the consumer purchase, he is registered as regular. Besides, the consumers who do not know each other, can share information, suggest products, spread the news.

• The KIPS Transactions:PartD
• /
• v.13D no.2 s.105
• /
• pp.279-286
• /
• 2006

One of the widely used methods for product recommendation in Internet storefronts is matching product features against target customer profiles. When using this method, it's very important to choose a suitable subset of features for recommendation efficiency and performance, which, however, has not been rigorously researched so far. In this paper, we utilize a dataset collected from a virtual shopping experiment in a Korean Internet book shopping mall to compare several popular methods from other disciplines for selecting features for product recommendation: the vector-space model, TFIDF(Term Frequency-Inverse Document Frequency), the mutual information method, and the singular value decomposition(SVD). The application of SVD showed the best performance in the analysis results.

• Information Systems Review
• /
• v.12 no.3
• /
• pp.49-73
• /
• 2010

The lack of customer satisfaction and trust remains a key barrier to electronic commerce. From the standpoint of online merchants, it is critical to build consumer trust by lessening sources of apprehensions and uneasiness associated with online transactions. This paper explores the relationships between customer satisfaction and intermediary's trustworthiness factors in B2C e-marketplaces. It also aims at examining the effects of consumer characteristics, including propensity to trust and Internet shopping self-efficacy, upon trust and purchase intentions. To meet the research objectives, an empirical study has been conducted by surveying 223 active e-marketplace buyers in Korea. The findings of the present research indicate that customer satisfaction positively affects all the three attributes of trustworthiness (i.e., competence, benevolence, and integrity), and more specifically it has a quite strong association with benevolence. In addition, propensity to trust has no significant influence on trust or purchasing intentions, and only affects benevolence and integrity with no direct effect on competence. Finally, Internet shopping self-efficacy was found to affect both trust and purchasing intentions, suggesting that e-marketplaces seek an online strategy designed to strengthen loyalty for customers with high self-efficacy, while they use a strategy to improve the usability and usefulness of their website to attract customers with low self-efficacy. The paper concludes with implications and directions for future research.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.2
• /
• pp.197-206
• /
• 2012

A exisiting recommedation system using association rules has the problem, such as delay of processing speed from a cause of frequent scanning a large data, scalability and accuracy as well. In this paper, using a Implicit method which is not used user's profile for rating, we propose the personalized recommendation system which is a new method using the FP-tree mining based on RFM. It is necessary for us to keep the analysis of RFM method and FP-tree mining to be able to reflect attributes of customers and items based on the whole customers' data and purchased data in order to find the items with high purchasability. The proposed makes frequent items and creates association rule by using the FP-tree mining based on RFM without occurrence of candidate set. We can recommend the items with efficiency, are used to generate the recommendable item according to the basic threshold for association rules with support, confidence and lift. 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.

• The Journal of the Korea Contents Association
• /
• v.15 no.5
• /
• pp.132-141
• /
• 2015

Smart television(TV) is replacing the traditional television model and the importance of user experience(UX) is rising. User experience evaluates the emotion state of users such as immersion, pleasure, and interest. User experience together with usability is a principle to be considered as for designing a smart television. It contributes to improve user satisfaction and lead to the long-term purchase. User experience is more difficult to measure than usability, because UX evaluation requires to biological and psychological techniques. However, the disadvantages of these physiological and psychological techniques require high experimental costs and the restriction of experimental environment. The objective of this paper is first to review conventional methods regarding UX evaluation and suggests a new method for measuring the UX of smart TV which detects keywords related emotional representation. The text is acquired from purchase postscripts of smart TV in the Internet shopping malls. This method costs less than the questionnaire survey to detect emotion.

• Journal of Korea Multimedia Society
• /
• v.7 no.9
• /
• pp.1219-1232
• /
• 2004

Recently, the web sites, such as e-business sites and shopping mall sites, deal with lots of catalog image information and contents. As a result, it is required to support semantic-based image retrieval efficiently on such image data. This paper presents a semantic-based image retrieval system, which adopts XML and Fuzzy technology. To support semantic-based retrieval on product catalog images containing multiple objects, we use a multi-level metadata structure which represents the product information and semantics of image data. To enable semantic-based retrieval on such image data, we design a XML database for storing the proposed metadata and study how to apply fuzzy data. This paper proposes a system, generate the fuzzy data automatically to use the image metadata, that can support semantic-based image retrieval by utilizing the generating fuzzy data. Therefore, it will contribute in improving the retrieval correctness and the user's satisfaction on semantic-based e-catalog image retrieval.

• The KIPS Transactions:PartB
• /
• v.9B no.5
• /
• pp.579-586
• /
• 2002

The edge descriptor proposed by MPEG-7 standard is a representative approach for the contents-based image retrieval using the edge information. In the edge descriptor, the edge information is the edge histogram derived from a gray-level value image. This paper proposes a new method which extracts color edge information from color images and a new approach for the contents-based image retrieval based on the color edge histogram. The poposed method and technique are applied to image retrieval of the e-catalogue. For the evaluation, the results of image retrieval using the proposed approach are compared with those of image retrieval using the edge descriptor by MPEG-7 and the statistics shows the efficiency of the proposed method. The proposed color edge model is made by combining the R,G,B channel components vectorially and by characterizing the vector norm of the edge map. The color edge histogram using the direction of the color edge model is subsequently used for the contents-based image retrieval.

• Journal of Digital Contents Society
• /
• v.15 no.6
• /
• pp.711-719
• /
• 2014

Along with the advent of ubiquitous computing environment, it is becoming a part of our common life style that the demands for enjoying the wireless internet using intelligent portable device such as smart phone and iPad, are increasing anytime or anyplace without any restriction of time and place. The recommending service becomes a very important technology which can find exact information to present users, then is easy for customers to reduce their searching effort to find out the items with high purchasability in e-commerce. Traditional mining association rule ignores the difference among the transactions. In order to do that, it is considered the importance of type of merchandise or service and then, we suggest a new recommending service using mining sequential pattern based on weight to reflect frequently changing trends of purchase pattern as time goes by and as often as customers need different merchandises on e-commerce being extremely diverse. To verify improved better performance of proposing system than the previous systems, we carry out the experiments in the same dataset collected in a cosmetic internet shopping mall.

• The Journal of the Korea Contents Association
• /
• v.5 no.4
• /
• pp.28-35
• /
• 2005

This paper examines empirically the effect of mileage program in e-Business on brand loyalty, and the mediating role of customers' trust and relational commitment. The results show that customer's benefits and convenience of the program significantly influences positively customer's trust. In addition, customer's trust also influences positively relational commitment, and relational commitment significantly influences positively brand loyalty. Thus, trust and relational commitment should be considered in the mileage program to improve the brand loyalty of internet shopping mall. Implications and limitations of this study are suggested.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.2 no.1
• /
• pp.59-66
• /
• 2001

Networked Virtual Reality systems provide a consistent virtual world to the users, possibly ditributed across long distance, and have been widely applied in the military war game, network game. edutainment, architectural areas, and shopping mall etc. Large processing requirements. however. made these systems be mainly researched on the platforms of high-performence system graphics workstations. This study paper Presents several problems when networked virtual reality systems are implemented on commodity Internet : two problems related with 3D graphical Processing, and the other related with network bandwidth and transmission delay. We also suggest solutions to these problems and analyze their performance effect based on an architectural simulation application.