Title :
Study on Recommendation Algorithm Based on Artificial Immune Network
Author :
Lu, Lu ; Sui Jianjun
Author_Institution :
Fac. of Comput., Guangdong Univ. of Technol., Guangzhou, China
Abstract :
A recommendation algorithm based on artificial immune network is proposed to deal with the problems of data sparsity and scalability in recommendation technology in the paper. The algorithm can reduce data sparsity and improve the accuracy by using its own mechanisms for dynamic regulation of the immune. The experimental results show that the algorithm has improved the recommend accuracy and has some practical significance.
Keywords :
artificial immune systems; data mining; recommender systems; artificial immune network; data scalability; data sparsity; recommendation algorithm; Accuracy; Algorithm design and analysis; Cloning; Data mining; Immune system; Prediction algorithms; Training; aiNet; immune network; recommendation;
Conference_Titel :
Computer Science and Electronics Engineering (ICCSEE), 2012 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-0689-8
DOI :
10.1109/ICCSEE.2012.399
