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Block Based Web Page Feature Selection with Neural Network

  • Conference paper
Advances in Computer Science, Environment, Ecoinformatics, and Education (CSEE 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 215))

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Abstract

To extract the feature of web page accurately is one of the basic topics of Web Data Mining. Considering the structure of web page, a block based feature selection method was imported in this article. A neural network could be used to recognize the priorities of different web page block and then the VPDom tree was built up. The experiment proves that Block Based Feature Selection could filter the “noisy” and enhance the main content of the web page.

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© 2011 Springer-Verlag Berlin Heidelberg

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Jin, Y., Liu, R., He, X., Huang, Y. (2011). Block Based Web Page Feature Selection with Neural Network. In: Lin, S., Huang, X. (eds) Advances in Computer Science, Environment, Ecoinformatics, and Education. CSEE 2011. Communications in Computer and Information Science, vol 215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23324-1_36

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  • DOI: https://doi.org/10.1007/978-3-642-23324-1_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23323-4

  • Online ISBN: 978-3-642-23324-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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