Web content mining for market intelligence acquiring from b2c websites

  • Authors:
  • Danxiang Ai;Yufeng Zhang;Hui Zuo;Quan Wang

  • Affiliations:
  • School of Information Management, Wuhan University, Hubei, P.R. China;School of Information Management, Wuhan University, Hubei, P.R. China;School of Economics and Management, Wuhan University, Hubei, P.R. China;School of Information Management, Wuhan University, Hubei, P.R. China

  • Venue:
  • WISE'06 Proceedings of the 7th international conference on Web Information Systems
  • Year:
  • 2006

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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.