Artificial Immunity-Based Discovery for Popular Information in WEB Pages

  • Authors:

  • Caiming Liu;Xiaojie Liu;Tao Li;Lingxi Peng;Jinquan Zeng;Hui Zhao

  • Affiliations:

  • School of Computer Science, Sichuan University, 610065 Chengdu, China;School of Computer Science, Sichuan University, 610065 Chengdu, China;School of Computer Science, Sichuan University, 610065 Chengdu, China;School of Computer Science, Sichuan University, 610065 Chengdu, China;School of Computer Science, Sichuan University, 610065 Chengdu, China;School of Computer Science, Sichuan University, 610065 Chengdu, China

  • Venue:
  • ICCS '07 Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

An artificial immunity-based discovery method for popular information is proposed. Principles of evolution and concentration of antibodies in artificial immune system are simulated. Key words in web pages are extracted and simulated as antibody and antigen. Antibodies are evolved and excreted dynamically. Concentration of antibodies is computed to attain accurately the degree of popular measurement in quantity. The proposed method improves the intelligent degree of information discovery and provides a new way to discover WEB information.