The Webpage Classification Research of Maximum Entropy Basing on Knowledge Tree

Zuo Jiang; Li Tong; Hong Zhi Liao; Na Zhao; Zhi Tao Fu

doi:10.4028/www.scientific.net/AMM.291-294.2853

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 291-294The Webpage Classification Research of Maximum...

The Webpage Classification Research of Maximum Entropy Basing on Knowledge Tree

Abstract:

Webpage classifier is one of the most important technology in search engine. In this paper，the structural features of webpage have been analyzed. basing on the structure of knowledge Tree, Maximum Entropy Model is applied to the webpage classification. Compared with other approaches, the experimental results show our approach achieve to higher recall and precision.

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Periodical:

Applied Mechanics and Materials (Volumes 291-294)

Pages:

2853-2858

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.291-294.2853

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Online since:

February 2013

Authors:

Zuo Jiang, Li Tong, Hong Zhi Liao, Na Zhao, Zhi Tao Fu

Keywords:

Knowledge Tree, Maximum Entropy Model, Search Engine

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