NDLI: Research on Forecasting the Dangerous Level to Illegal Email Based on Integrated Immune Evolution Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Ke-Jian Wang Xian-Zhong Han Xin-Sheng Sun Shu-Hui Chang Hui-Fang Qi
Copyright Year	2006
Description	Author affiliation: Fac. of Inf. Sci. & Technol., Agric. Univ. Hebei, Baoding (Ke-Jian Wang; Xian-Zhong Han; Xin-Sheng Sun; Shu-Hui Chang)
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
Sponsorship	IEEE Syst., Man and Cybernetics Hebei Univ.
Starting Page	2112
Ending Page	2116
File Size	205338
Page Count	5
File Format	PDF
ISBN	1424400619
DOI	10.1109/ICMLC.2006.258353
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-13
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Immune system Evolution (biology) Robust stability Postal services Information processing Organisms Machine learning algorithms Agriculture Protection Fault tolerant systems illegal email Integrated Immune Evolutionary Algorithm The model of forecasting the dangerous level TF-IDF formula
Content Type	Text
Resource Type	Article

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