• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.4
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• pp.980-985
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• 2008

The environment of IT is, currently, on its developing process to the period of web 2.0 and mashup which not only enable computer and internet to be utilized like the water or the air, but also be a new motivating force for its advance. One of the biggest changes of the industry that lies ahead is consolidated transportation. However, no party outstands as the leading party for nationwide improvement of logistics, nor does the right analysis and design for it. Therefore, successful nationwide logistics model is yet to exist. This study provides individual parties, which consider consolidated transportation model as their implementation and design of the framework, with instructions for logistics information system so that they could be competitive in the market. It also helps companies collect user requirements for logistics information system consolidated transportation, and utilize it for its development. Finally, the study provides a implementation and design of pilot system for consolidated transportation model.

• Journal of Digital Contents Society
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• v.2 no.1
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• pp.1-7
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• 2001

The authoring systems for digital contents using multimedia technologies ate requested in many fields such as education, medical science, entertainment market e-commerce and etc. Especially, the emergence of cyber universities and the rapid expansion of on-line education market require the effective contents authoring systems, which have various functions to generate the qualified contents. Therefore, many systems arc developed and currently used. However, since the developed systems considered only the developer's convenience, the generated digital contents by using these systems are failed to draw tile users'(or learners') active interaction with contents. That is, since the users just watch the contents like watching a drama or a film, it causes many problems in delivering the contents effectively or in evaluating the users. This paper presents, develops, and implements the new contents authoring system by using programing languages and/or software tools. The presented, developed, and implemented system mimics the face-to-face education in off-line system, induces the users' active interaction with contents, and continuous evaluation to the users.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.1
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• pp.147-155
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• 2003

The diffusion of internet infrastructure and a fast increase of Population to use it is becoming a base of the service that can use various information, data and digital contents which were provided through off-line physically and used. Recently, the. techniques for copy deterrence and copyright protection have been important in e-commerce because various contents in digital form can be duplicated easily. The Access Control(AC) technique that only a user having the qualifications can access and use contents normally has been studied. The Conditional Access System(CAS) used in a satellite broadcasting md Digital Right Management System(DRMS) used for contents service are representative models of current commercialized access control. The CAS and DRM can be considered as an access control technique based on the payment based type(PBT). This paper describe the access control method of payment free type(PFT) suggested in ［5］ which are independent on the payment structure. And then we suggest a new access control method of payment free type which is more efficient than the previous one.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Journal of information and communication convergence engineering
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• v.18 no.2
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• pp.123-131
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• 2020

After observing that most tourists plan to complete their visits to multiple cultural heritage sites within one day, we surmised that for many museum visitors, the foremost thought is with regard to the amount of time is to be spent at each location and how they can maximize their enjoyment at a site while still balancing their travel itinerary? Recommendation systems in e-commerce are built on knowledge about the users' previous purchasing history; recommendation systems for museums, on the other hand, do not have an equivalent data source available. Recent solutions have incorporated advanced technologies such as algorithms that rely on social filtering, which builds recommendations from the nearest identified similar user. Our paper proposes a different approach, and involves providing dynamic recommendations that deploy social filtering as well as content-based filtering using term frequency-inverse document frequency. The main challenge is to overcome a cold start, whereby no information is available on new users entering the system, and thus there is no strong background information for generating the recommendation. In these cases, our solution deploys statistical methods to create a recommendation, which can then be used to gather data for future iterations. We are currently running a pilot test at Chao Samphraya national museum and have received positive feedback to date on the implementation.

• Journal of Information Technology Services
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• v.7 no.2
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• pp.1-12
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• 2008

The development of IT and explosively growing number of Internet users are rapidly spreading and developing e-commerce, while creating diverse on-line transaction methods such as a negotiation, a reverse auction, and a bid. Among these transaction methods, the transactions by means of a negotiation are being made for goods that have no posted price. In particular, the transactions by means of a negotiation are expected to be widely used in the B2B. In order to determine their transportation costs, shippers usually make negotiations with many transporters and logistics companies. And before long, these negotiations are expected to be made on an on-line automated negotiation system. Because of this, this study has tried to develop an automated negotiation methodology that is absolutely necessary for an on-line automated negotiation. This study has estimated and selected the evaluation functions for multi-lateral negotiators' proposals, thus developing an automated negotiation methodology. As a result of this study, a new direction for an automated negotiation has been suggested. Also we expect that this study will be widely used in the automated negotiation of diverse fields.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.1010-1014
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• 2010

Article-related product recommender system is an emerging e-commerce service which recommends items based on association in contexts between items and articles. Current services recommend based on the similarity between tags of articles and items, which is deficient not only due to the high cost in manual tagging but also low accuracies in recommendation. As a component of novel article-related item recommender system, we propose a new method for tagging item images based on pre-defined categories. We suggest a hypernetwork-based algorithm for learning association between images, which is represented by visual words, and categories of products. Learned hypernetwork are used to assign multiple tags to unlabeled item images. We show the ability of our method with a product set of real-world online shopping-mall including 1,251 product images with 10 categories. Experimental results not only show that the proposed method has competitive tagging performance compared with other classifiers but also present that the proposed multi-tagging method based on hypernetworks improves the accuracy of tagging.

• International Commerce and Information Review
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• v.18 no.3
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• pp.3-21
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• 2016

The thesis examines genealogical study of various aspects to overcome lots of problems which come by when we execute SWIFTNet TSU BPO. Practical implications regarding the innovation of electronic trade infrastructure are as follows. First, the shipping documents in the SWIFTNet TSU BPO are directly sent to an importer by an exporter after the baseline is confirmed. With this process itself, therefore, the bank cannot secure the account receivable. When initiating the SWIFTNet TSU BPO deal, it is needed to set regulations on the bank's account receivable security in the contract. Second, the SWIFTNet TSU BPO should also have an institutionally unified sharing platform with security, stability and convenience. It other words, it is needed to develop services which meet e-payment paradigm and international environments through continued analysis on market changes and flow. Third, the SWIFTNet TSU is useful in terms of promptness, reduction of risk in foreign exchange payment, cost reduction. Therefore, the SWIFT should be perfectly united and linked among the banks, importer and exporter to make the SWIFTNet TSU more convenient in countries around the world. Fourth, the SWIFT should be approached from the aspect of expansion of network and creation of a new business model through analysis on these problems with a worldwide perspective. At the same time, it is necessary to build a cooperative system to share information and promote comprehensive management for efficient operation.

• Journal of Broadcast Engineering
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• v.14 no.4
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• pp.463-474
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• 2009

By employing the subscriber concept in broadcasting services, IPTV (Internet Protocol Television) operators provide various grades of services to subscribers based on the billing level of the subscribers. With the income from subscribers for a basis, IPTV operators plan to provide high quality services. Since Web browser-based IPTV provides T-commerce and E-commerce services as well as television services, users may frequently visit other service domains to buy goods or content. To provide the user with charged or private services, these service domains request authentication of user. The existing authentication system is not appropriate for the IPTV service environment because the environment unavoidably forces the user to cross from one authentication-based service domain to another. Single sign-on provides a user with transparent authentication services by enabling an authenticated user to move between authentication-based service domains without any re-authentication. Like this distributed environment, since the IPTV service environment also provides a variety of authentication-based services, transparent authentication service needs to be provided to subscribers who want to access charged or private services. In this paper, we propose a new user authentication scheme for the IPTV environment. This scheme integrates the Security Assertion Markup Language (SAML), which is a standard for XML-based single sign on. We validate this scheme using a simple use case scenario.