Immune Network Based Text Clustering Algorithm

Abstract

The principles of the immune system and Monoclonal were introduced briefly. Focused on the text expressed by the vector space model which was processed by semantic computation, an adaptive polyclonal clustering algorithm was proposed. Firstly, the calculation method was defined for the affinity between antibody and antigens and the affinity of antibodies, the genetic operation factors were designed, replacement, inverse, colonel, crossover, mutation, death, concatenate and clustering included, secondly, the process was given, and lastly, the clustering processes and analysis were done based on the text sets in a corpora. The experiments verifies that the algorithm proposed above can get the rational clustering number and have a better correct identification rate and recall rate.