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International Workshop on Data Engineering Issues in E-Commerce
Optimizing the Catalog Search Process for E-Procurement Platforms
Tokyo, Japan
April 09-April 09
ISBN: 0-7695-2401-X
Sven D?ring, Faculty of Applied Computer Science, University of Augsburg, Germany
Stefan Fischer, Faculty of Applied Computer Science, University of Augsburg, Germany
Werner Kie?ling, Faculty of Applied Computer Science, University of Augsburg, Germany
Timotheus Preisinger, Faculty of Applied Computer Science, University of Augsburg, Germany

Many e-procurement platforms support XML-based ecatalogs combined with standardized feature descriptions. Beyond the usual keyword search this opens the arena for attribute-based search engines, including parametric search and preference search. We analyze the impact of different search techniques for such ecatalogs on the overall search process costs. It turns out that preference search has a high potential to significantly reduce the process costs. A large-scale use case with the MAN2B e-procurement platform supports our claim. We identify improvements achievable by using preference search, in particular less navigation steps during the product search and better search results due to the BMO query model. Expensive cases, where frustrated users accept bad search results or phone up the company's purchasing department, should decrease significantly. This in turn will enable the purchasing department to focus more on strategic issues like supplier relationship management than on operative issues as it still happens widely today.

Citation:
Sven D?ring, Stefan Fischer, Werner Kie?ling, Timotheus Preisinger, "Optimizing the Catalog Search Process for E-Procurement Platforms," deec, pp.39-48, International Workshop on Data Engineering Issues in E-Commerce, 2005
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