• Journal of Korea Multimedia Society
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• v.10 no.9
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• pp.1106-1116
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• 2007

Recently e-commerce trade on the web has grown rapidly in scale and complexity, just as web site designs and web servers have become more complicated. In view of these complexities, it is obviously difficult to analyse web user's data since they web users employ so many different web paths. The existing association rule investigation algorithms identify all items with a high correlation. However even though users often only want to find items in which they have interest, it is still difficult to find the rules they want out of all of the many association rules found by existing algorithms. In this paper, we propose a system linking each node with the sequence association rule, linking all routes after finding a path corresponding to a user with the association rule-one of the data mining techniques which identify user patterns in web user paths. The suggested system helps us construct individualized or customer-subdivided sites using the sequence association rule in order to harmonize the paths of web users with user characters.

• The Journal of Society for e-Business Studies
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• v.14 no.3
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• pp.131-151
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• 2009

Natural interface is important to select and provide the services in ubiquitous smart space such as u-plant, u-distribution. Augmented Reality(AR) has recently begun to receive attention as a realization tool for natural interface. AR provides virtual object on real environment and it differs from virtual reality. When AR is used, it has advantage to provide information intuitively and collaboratively. However AR is rarely used in e-commerce domain of ubiquitous smart space, and it has limitation which predefined information and services provide in a static manner. Hence, the purpose of this paper is to propose a methodology of AR based e-commerce which provides personalized association service by considering user's dynamic context. To do so, association algorithm is developed based on Rescorla-Wagner model and Galton's free association test.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.189-199
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• 2009

The amount of information on the Web is explosively growing as the Internet gains in popularity. However, only a small portion of the information on the Web is truly relevant or useful to the user. Thus, offering suitable information according to user demand is an important subject in information retrieval. In e-commerce, the recommender system is essential to revitalize commercial transactions, raise user satisfaction and loyalty towards the information provider. The existing recommender systems are mostly based on user data collected at servers, so user data are dispersed over several servers. Therefore, web servers that lack sufficient user behavior data cannot easily infer user preferences. Also, if the user visits the server infrequently, it may be hard to reflect the dynamically changing user's interest. This paper proposes a novel personalization system analyzing the user preference based on web documents that are accessed by the user on a user device. The system also identifies non-content blocks appearing repeatedly in the dynamically generated web documents, and adds weight to the keywords extracted from the hyperlink sentence selected by the user. Therefore, the system establishes at an early stage recommendation strategies for the web server that has little user data. Also, user profiles are generated rapidly and more accurately by identifying the information blocks. In order to evaluate the proposed system, this study collected web data and purchase history from users who have current purchase activity. Then, we computed the similarity between purchase data and the user profile. We confirm the accuracy of the generated user profile since the web page containing the purchased item has higher correlation than other item pages.

• The KIPS Transactions:PartC
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• v.9C no.3
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• pp.351-358
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• 2002

Recently, personal business styles have been rapidly changed into e-business due to the rapid progress and deployment of Internet. As a result of the change, new and safe ways of payment such as electronic wallet, electronic money and electronic check have been developed and introduced. In this paper a secure and user-friendly payment method is addressed. One of most important reasons why newly developed safe payment methods are not widely used in e-business is lack of convenience for the users. On the other hand credit card based payment, which is traditional one, is the most prevailing due to the user-friendliness. However this payment also has some problem in sense of security. In this paper, we design and implement a secure credit card-based payment system using one-time credit information. The main features are "payment information must be new", "can use the old credit system", and "do not require client software".

• The Journal of Korean Association of Computer Education
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• v.14 no.4
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• pp.63-70
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• 2011

Recommender systems, which predict and recommend items that may possibly draw users' interests, have been applied in various fields as e-commerce systems are widespread. Collaborative filtering, one of the major methodologies of recommender systems, recommends either items similar to those preferred by the user, or items preferred by the other similar user. Therefore, two problems determine its performance; one is correct estimation of similarity and the other is predicting the real rating of the recommended item. This study addresses the latter problem. Previous studies predict the real rating based on the mean of the ratings, but this study proposes a prediction based on the range of the ratings and investigates its performance through experiments. As a result, it is demonstrated that the proposed method improves the mean absolute error significantly, compared to the previous method.

• Journal of Digital Convergence
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• v.15 no.9
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• pp.223-230
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• 2017

In the current wireless Internet environment, using a mobile device to quickly access a web site is closely related to measuring the performance of a website. When accessing a website, the user has a long time to access the website and has no access to the website.In this case, the performance of the web site should be improved by measuring and analyzing the performance of the connection delay due to a problem of the web site.Among the performance measurement factors of Web sites, Web page loading time is a very important factor for a successful service business in the situation where most of e-commerce business is being developed as a web-based service.An open source tool was analyzed to analyze the performance of the e-commerce web page to present problems, software optimization methods and hardware optimization methods. Applying two optimization methods to suit the environment will enable stable and e-commerce websites.

• Journal of Information Technology Applications and Management
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• v.25 no.2
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• pp.53-72
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• 2018

This empirical study explored characteristics that affect the usefulness of online reviews, in the China e-commerce platform, and implemented multiple regressions to find factors that significantly influence on product sales, ultimately. Till now, prior studies have continuously revealed what factor affects usefulness of online review or product sales, only in respective terms. The point of our study is that we built two-level regression models, thereby being able to comprehensively analyze these two different targets. Before plunging into running regressions, we carefully collected 192,764 online review data for 200 products extracted from the Jingdong, the second biggest e-commerce platform in China. Also, we gathered "review sentimental scores" variable from each review and used that one as a core variable in our regression model, thus we were able to implement both quantitative and qualitative research. The evidences from the two-level regression models showed that the extent to which a product is experience good positively affects both usefulness of a review and product sales, again the usefulness of a review contributes to product sales in sequence. Also, the property of experience good has interaction effect on both for two-level regression models. Our main findings highlight the importance of role of online review to business performance of e-commerce firms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2948-2966
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• 2014

To promote recommendation services through prediction quality, some privacy-preserving collaborative filtering solutions are proposed to make e-commerce parties collaborate on partitioned data. It is almost probable that two parties hold ratings for the same users and items simultaneously; however, existing two-party privacy-preserving collaborative filtering solutions do not cover such overlaps. Since rating values and rated items are confidential, overlapping ratings make privacy-preservation more challenging. This study examines how to estimate predictions privately based on partitioned data with overlapped entries between two e-commerce companies. We consider both user-based and item-based collaborative filtering approaches and propose novel privacy-preserving collaborative filtering schemes in this sense. We also evaluate our schemes using real movie dataset, and the empirical outcomes show that the parties can promote collaborative services using our schemes.

• The Journal of Society for e-Business Studies
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• v.4 no.3
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• pp.159-178
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• 1999

As Electronic Commerce is getting larger, the volume of Internet-based commerce by enterprise is also getting larger. This phenomenon applies to Internet EDI, Global Internet Business, and CALS information services. In this paper, a new type of cryptographic key recovery mechanism satisfying requirements of business environment is proposed. It is also applied to enterprise information infrastructure for managing employees' task related to handling official properties of electronic enterprise documents exchange. This technology needs to be complied to information management policy of a certain enterprise environment because behavior of cryptographic key recovery can cause interruption of the employees' privacy. However, the cryptographic key recovery mechanism is able to applied to any kind of information service, the application areas of key recovery technology must be seriously considered as not disturbing user's privacy It will depend on the policy of enterprise information management of a specific company.

• Journal of Digital Contents Society
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• v.2 no.2
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• pp.139-145
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• 2001

As e-commerce has been activated and internet has been used as usual, higher efficient search engine must be used to promote the value of information and take possession of the market place. all e-commerce user seller and buyer want to competitive goods Although these needs, search results are still much to be desired. In this paper, I will suppose two ideas which are abbreviation result and making blacklist. Abbreviation result is to hide results with common factors and making blacklist is to reduce null links of search results, which makes many useless results. This routine is made of making blacklist, check list, reduce list and append list.