Document classification with multi-layered immune principle

  • Authors:
  • Chunlin Liang;Yindie Hong;Yuefeng Chen;Lingxi Peng

  • Affiliations:
  • Software School, Guangdong Ocean Univ., Zhanjiang, China;Software School, Guangdong Ocean Univ., Zhanjiang, China;Software School, Guangdong Ocean Univ., Zhanjiang, China;School of Computer Science, Guangzhou University, Guangzhou, China

  • Venue:
  • ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

Automatic document classification is helpful in both organizing and finding information on huge resources A novel multi-layered immune based document classification algorithm is presented First, we represent the definition of the immune cells, antibody, antigen, and discuss the architecture of multi-layered immune system Second, we evolve the dynamic models of immune response, immune regulation and immune memory, and establish the corresponding equations Finally, we implement the simulation experiments, and compare the results with those obtained using the best methods for this application Experiments show that the algorithm has higher classification accuracy than other document classification methods, and the attractive features such as diversity, self-learning, adaptive and robust etc It provides a novel solution for document classification.