• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.39-43
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• 2004

A research shows that a new category of software, Collaborative Product Commerce (CPC), is now emerging, allowing discrete manufacturers to once again distinguish themselves on their products and innovations. CPC permits discrete manufacturers to significantly improve the core processes around the management functions associated with the complete product life cycle that are the basis of their existence. As a way to develop computing tools of CPC to support a design process of product, a web-based design supporting system was constructed in the paper. The system consists of C-Product system and Net Meeting Communication system to improve communications between designers and persons for verification of design. The product data files of C-Product system were designed by Pro/Engineer and converted to 3D Viewer format for being used in the web browser. Also, Net Meeting Communication system and Database were developed using ASP and Microsoft SQL 2000 Server to share diverse files that can be utilized to design on the web in real time.

• Proceedings of the CALSEC Conference
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• 2001.02a
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• pp.11-30
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• 2001

Session Agenda ㆍ E-Business Economy - B2B · What is C-Commerce？ - Marketplace or Businessplace？ ㆍ C-Commerce Business Models - Horizontal, Industry, Private ㆍ C-Commerce via Exchange Solution Models - Marketplace Exchange - Supply Chain Exchange - Product Development Exchange ㆍ Integration is key... NOT Functionality(omitted)

• Proceedings of the Korea Information Assurance Society Conference
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• 2004.05a
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• pp.119-124
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• 2004

The service oriented architecture (SOA) is gaining more momentum with the advent of Web services on internet. A programmable and machine accessible Web is the vision of many, and might represent a step towards the semantic Web. However, security is a crucial requirement for the serious usage and adoption of the Web services technology. This paper proposes design goals for an distributed access control model for CPC(Collaborative Product Commerce). It then design a processor model for CPC components, along with web services standard and concept that can be used as a basis to design an access control processor independent of a particular CPC service implementation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.332-339
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• 2005

We developed a similar product recommendation system for implementing a collaborative commerce model between the cooperating companies. The system is based on a similar product finding algorithm. The main idea of the proposed algorithm is using a multi-attribute decision making(MADM) to find the utility values of products in same product class of the companies. Based on the values we determine what products are similar. The system helps the companies to recommend products in accordance with the customer's preferences regarding product specifications.

• The Journal of Society for e-Business Studies
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• v.9 no.4
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• pp.19-36
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• 2004

This paper suggests a business process between the collaborative companies that want to extend globally sales and delivery service with restricted physical branches in their own areas. The companies integrate their business processes for sales and delivery services using a shared product taxonomy table. In order to perform the collaborative processes, they need the algorithm to exchange their own products. We suggest a similar product finding algorithm to compose the product taxonomy table that defines product relationships to exchange them between the companies. The main idea of the proposed algorithm is using a multi-attribute decision making (MADM) to find the utility values of products in a same product class of the companies. Based on the values we determine what products are similar. It helps the product manager to register the similar products into a same product sub-category. The companies then allow consumer to shop and purchase the products at their own residence site and deliver them or similar products to another sites.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.2
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• pp.27-39
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• 2006

The Collaborative Filtering (CF) is one of the popular techniques for personalization in e-commerce storefronts. For CF-based recommendation, every customer needs to provide subjective evaluation ratings for some products based on his/her preference. Also, if an e-commerce site recommends a new product, some customers should rate it. However, there is no in-depth investigation on the impacts on recommendation performance of two number of ratings, i.e. the number of ratings of an individual customer and the number of ratings of an item, even though these are important factors to determine performance of CF methods. In this study, using publicly available EachMovie data set, we empirically investigate the relationships between the two number of ratings and the performance of CF. For the purpose, three analyses were executed. The first and second analyses were performed to investigate the relationship between the number of ratings of a particular customer and the recommendation performance of CF. In the third analysis, we investigate the relationship between the number of ratings on a particular item and the recommendation performance of CF. From these experiments, we can find that there are thresholds in terms of the number of ratings below which the recommendation performances increase monotonically. That is, the number of ratings of a customer and the number of ratings on an item are critical to the recommendation performance of CF when the number of ratings is less than the thresholds, but the value of the ratings decreases after the numbers of ratings pass the thresholds. The results of the experiments provide insight to making operational decisions concerning collaborative filtering in practice.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.211-220
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• 2004

This paper suggests a collaborative business process between the companies that each has a restricted physical branch in its own area and wants to extend globally sales and delivery service. The companies integrate their business processes for sales and delivery using a shared product taxonomy table. We also suggest a similar product finding algorithm to make the product taxonomy table that defines product relationships to exchange them between the companies. The main idea of the proposed algorithm is using a multi-attribute decision making (MADM) to find the utility values of products in a same product class of the companies. Using the values we determine what products are similar. It helps the product manager to register the similar products into a same product sub-category. The companies then allow consumer to shop and purchase the products at their own residence site and deliver them or similar products to another sites.

• CDE review
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• v.8 no.1
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• pp.52-57
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• 2002

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1252-1268
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• 2003

There is a big change in Electronic Commerce. With little or no profit projected for the foreseeable future with the dotcom companies, Internet venture capitalists are looking for new business models. They are now turning to B to B Electronic Commerce. It is expected that B to B Electronic Commerce will be more active than B to C in the very near future. In the future B to B Electronic Commerce will move to include collaborative Electronic Commerce which includes product development, engineering, material procurement, and management. Even though the solution to this multidimensioal and complicated process may take some time, a total solution to this will dramatically change the landscape of Electronic Commerce. Thus the various corporations must work together to find the total solution that will build this infrastructure.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.2
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• pp.74-80
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• 2013

In this study, a novel and flexible recommender system was developed, based on product taxonomy and usage patterns of users. The proposed system consists of the following four steps : (i) estimation of the product-preference matrix, (ii) construction of the product-preference matrix, (iii) estimation of the popularity and similarity levels for sought-after products, and (iv) recommendation of a products for the user. The product-preference matrix for each user is estimated through a linear combination of clicks, basket placements, and purchase statuses. Then the preference matrix of a particular genre is constructed by computing the ratios of the number of clicks, basket placements, and purchases of a product with respect to the total. The popularity and similarity levels of a user's clicked product are estimated with an entropy index. Based on this information, collaborative and content-based filtering is used to recommend a product to the user. To assess the effectiveness of the proposed approach, an empirical study was conducted by constructing an experimental e-commerce site. Our results clearly showed that the proposed hybrid method is superior to conventional methods.