DocumentCode :
484985
Title :
Key technologies research of network information filtering based on Improved Genetic Algorithms
Author :
Liu, Pei-Yu ; Zhu, Zhen-Fang ; Wei, Yong-qing
Author_Institution :
Shandong Normal Univ., Jinan
Volume :
1
fYear :
2008
fDate :
6-8 Oct. 2008
Firstpage :
88
Lastpage :
93
Abstract :
Along with the development of the Internet, how to manage and control network information resources effectively has become a hot research. In this paper, we discussed key technologies of network information filtering: feature selection and learning algorithm. Based on feature subset generated by feature selection would affect the filtering accuracy, we proposed an improved feature selection method CHIIDF, using this method to remove redundant features, then using annealing genetic algorithm to learn and to get user profile. Finally, we developed the system of network information filtering and analyzed the data that achieved good results.
Keywords :
Internet; genetic algorithms; information filtering; learning (artificial intelligence); CHIIDF method; Internet; annealing genetic algorithm; feature selection method; learning algorithm; network information filtering; network information resource management; Annealing; Data analysis; Filtering algorithms; Genetic algorithms; IP networks; Information filtering; Information filters; Information resources; Research and development management; Resource management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pervasive Computing and Applications, 2008. ICPCA 2008. Third International Conference on
Conference_Location :
Alexandria
Print_ISBN :
978-1-4244-2020-9
Electronic_ISBN :
978-1-4244-2021-6
Type :
conf
DOI :
10.1109/ICPCA.2008.4783655
Filename :
4783655
Link To Document :
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