Advertisement

Research and Design of Personalized Information Retrieval Based on Users’ Clustering

  • Yan Hu
  • Baohong Yu
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 169)

Abstract

With the description of the shortcomings of the existing popular search engines and the personalized information retrievals based on individuals, the personalized information retrieval based on users’ clustering was proposed, of which the key technologies of users’ clustering, user group dictionary, user search and sorting and so on were described in detail and it was proved by experiments that the personalized information retrieval based on users’ clustering improved the efficiency of the information retrieval.

Keywords

Search engines Personalized Users’ clustering User search Sorting Information retrieval 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Manning, C.D., Raghavan, P., Schutze, H.: Introduction to Information Retrieval. People’s Telecon Publishing House, Beijing (2010)Google Scholar
  2. 2.
    Jain, A.K., Dubes, R.C.: Algorithms for Clustering Data. Prentice-Hall, Inc. (1998)Google Scholar
  3. 3.
    Henzinger, M.R.: Hyperlink analysis for the Web. IEEE Internet Computing 5(1), 45–50 (2001)CrossRefGoogle Scholar
  4. 4.
    Zhu, M., Wang, J., Wang, J.: The Study of Feature Selection in the Web Page Classification. Computer Engineering 26(8), 35–37 (2000)Google Scholar
  5. 5.
    Wang, G., Xu, J.: TCBLSA: A New Method of Chinese Text Clustering. Computer Engineering 30(5), 21–22, 37 (2004)Google Scholar
  6. 6.
    Song, J., Wang, Y.: Improvement of the Robot Search Algorithm. Journal of The China Society For Scientific and Technical Information 21(2), 130–133 (2002)Google Scholar
  7. 7.
    Xing, C., Gao, F., Zhan, S.: A Collaborative Filtering Recommendation Algorithm Incorporated with User Interest Change. Journal of Computer Research and Development 44(2) (2007)Google Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.School of Computer Science and TechnologyWuhan University of TechnologyWuhanChina

Personalised recommendations