Abstract
Market Intelligence (MI) is information and knowledge relevant to an enterprise market decision-making process. MI acquiring is a key activity for enterprises to keep predominance in furious market competition. The quick-developed Internet provides abundant information resources, but there is a lack of effective new approaches and models for MI acquiring. In this paper, we concentrate on MI mining based on B2C websites. We develop a specialized B2C websites mining model by syncretizing technology of web mining, knowledge representation, data warehouse and metadata. We design a web content mining algorithm integrating several web mining methods, and perform the digital camera salesexperiments to validate it.
Supported by the National Natural Science Foundation of China (Grant No. 70573082).
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© 2006 Springer-Verlag Berlin Heidelberg
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Ai, D., Zhang, Y., Zuo, H., Wang, Q. (2006). Web Content Mining for Market Intelligence Acquiring from B2C Websites. In: Feng, L., Wang, G., Zeng, C., Huang, R. (eds) Web Information Systems – WISE 2006 Workshops. WISE 2006. Lecture Notes in Computer Science, vol 4256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11906070_16
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DOI: https://doi.org/10.1007/11906070_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-47663-4
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