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An Improved KNN Algorithm for Vertical Search Engines

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Book cover Web Information Systems and Mining (WISM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6988))

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Abstract

Secondary Data Processing deals the information further by re-crawling and categories based on the basic of structured data. It is the key researching module of Vertical Search Engines. This paper proposes an improved KNN algorithm for the categories. This algorithm achieves the responsiveness and the accuracy of vertical search by reducing the time complexity and accelerating the speed of classification. The experiment proved the improved algorithm has the better feasibility and robustness when it’s used in secondary data processing and participle of vertical search engines.

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Author information

Authors and Affiliations

  1. Institute of Information and electron, Zhejiang Sci-Tech University, Hangzhou, 310018, China

    Yubo Jia, Hongdan Fan, Guanghu Xia & Xing Dong

Authors
  1. Yubo Jia
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  2. Hongdan Fan
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  3. Guanghu Xia
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  4. Xing Dong
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Editor information

Editors and Affiliations

  1. Department of Computer and Inforamtion Science, University of Macau, Av. Padre Tomás Pereira, Taipa, Macau, China

    Zhiguo Gong

  2. School of Computer, Shanghai University, 200444, Shanghai, China

    Xiangfeng Luo

  3. College of Computer and Software, Taiyuan University of Technology, 030024, Taiyuan, China

    Junjie Chen

  4. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

  5. Department of Business Administration, Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

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© 2011 Springer-Verlag Berlin Heidelberg

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Jia, Y., Fan, H., Xia, G., Dong, X. (2011). An Improved KNN Algorithm for Vertical Search Engines. In: Gong, Z., Luo, X., Chen, J., Lei, J., Wang, F.L. (eds) Web Information Systems and Mining. WISM 2011. Lecture Notes in Computer Science, vol 6988. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23982-3_28

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  • DOI: https://doi.org/10.1007/978-3-642-23982-3_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23981-6

  • Online ISBN: 978-3-642-23982-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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