Title :
Research on Forecasting the Dangerous Level to Illegal Email Based on Integrated Immune Evolution Algorithm
Author :
Wang, Ke-jian ; Han, Xian-zhong ; Sun, Xin-sheng ; Chang, Shu-Hui ; Qi, Hui-fang
Author_Institution :
Fac. of Inf. Sci. & Technol., Agric. Univ. Hebei, Baoding
Abstract :
TF-IDF formula can represent effectively the text characteristics; the immunity system (TIS) has many characteristics, including the distributional protection, multiplicity, auto-adapted in the information processing, it is robust and expansibility, memory ability, fault-tolerant ability, dynamic stability as well as exceptionally examines. The paper analyzes characteristics of many illegal emails and researches artificial immune method, and introduces an artificial immune method of forecasting the dangerous level of illegal email, and gets good result
Keywords :
artificial intelligence; electronic mail; genetic algorithms; security of data; TF-IDF formula; illegal email; information processing; integrated artificial immune evolution algorithm; research forecasting; Agriculture; Application software; Constraint optimization; Evolution (biology); Evolutionary computation; Fault tolerant systems; Immune system; Information processing; Machine learning algorithms; Organisms; Postal services; Protection; Robust stability; Integrated Immune Evolutionary Algorithm; TF-IDF formula; The model of forecasting the dangerous level; illegal email;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258353
