Research of parallel recommendation algorithm based on idiotypic artificial immune network
基于独特型人工免疫网络的并行推荐算法的研究

This paper analyzed the problem of recommendation quality degradation resulting from the lack of the nearest neighborhood users set's diversity in Collaborated Filtering Algorithm, and then proposed the Parallel Immune Network Recommendation algorithm (PINR). The algorithm achieves improvement in the real-time response speed while maintaining the maximum diversity of neighborhood users set. The preliminary experiment shows the feasibility, correctness and the advantage in parallel computing of this algorithm.