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Architecture and performance of the rule based comparison shopping: delivery cost experience
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Source ACM International Conference Proceeding Series; Vol. 342 archive
Proceedings of the 10th international conference on Electronic commerce table of contents
Innsbruck, Austria
SESSION: B2C-3 table of contents
Article No. 32  
Year of Publication: 2008
ISBN:978-1-60558-075-3
Authors
Gyoo Gun Lim  Hanyang University, Seoul, Korea
Ju Young Kang  Ajou University, Suwon, Korea
Jae Kyu Lee  KAIST, Seoul, Korea
Dae Chul Lee  Hanyang University, Seoul, Korea
Sponsor
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
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ABSTRACT

Comparison shopping is one of the important ingredients in electronic commerce, because it saves time and efforts of searching for product information and costs. However, most shopping malls still rely on the simple data such as price and other descriptive specifications, and cannot support the services of comparing the exact cost which requires rule based computation such as delivery cost. The comparison of delivery costs requires tailored computation because each bookstore has different free shipping rules, delivery options, and shipping rates. The purpose of this paper is to propose a rule based comparison shopping framework using XRML(eXtensible Rule Markup Language) approach. We propose the architecture, named ConsiderD, of maintaining rules in the comparison portal site to be consistent with its original pages. We experiment the benefit of using the rule based exact computation in comparison of book buying with the result by estimated average price such as BestWebBuy.com does. The result shows that providing the benefit of rule based comparison is significant and the hidden information such as delivery cost can be effectively processed with XRML framework.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Gyoo Gun Lim: colleagues
Ju Young Kang: colleagues
Jae Kyu Lee: colleagues
Dae Chul Lee: colleagues