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Ranking-based business information processing: applications to business solutions and eCommerce systems

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2 Author(s)
Mao Chen ; IBM T. J. Watson Res. Center, Hawthorne, NY, USA ; Sairamesh, J.

Extracting crucial information in high volume business data efficiently are critical for enterprises to make timely business decisions and adapt accordingly. This paper proposes a novel ranking-based system that applies knowledge models and utility functions. In a case study for monitoring and analyzing automotive failures in aftermarket services, we shed a light on our ranking mechanism that combines objective business metrics and "subjective" domain knowledge. Our experiments using real-world data demonstrate that our methodology is capable of capturing macro view about business performance issues from a small but important fraction of information.

Published in:

E-Commerce Technology, 2005. CEC 2005. Seventh IEEE International Conference on

Date of Conference:

19-22 July 2005