一种基于聚类技术的免疫推荐算法

Immune Network Recommendation Algorithm Based on Clustering

在网络时代,如何通过为用户提供更加个性化的服务,提高其商品的吸引力,进而为企业带来更大的收益,成为了网站所面临的核心问题。通过对自然免疫学和人工免疫学理论的研究,着重讨论了将人工免疫网络技术应用于电子商务个性化推荐的思想,提出了使用形态空间模型对推荐技术及其存在问题的解释方法,并提出了聚类免疫推荐算法。实验结果表明:该算法能高效和准确地解决个性化推荐问题,具有很好的应用价值。

In internet times, it is an important challenge that how to make more personalized services for user, increase the attraction of the goods, and get greater benefits for company. Through studying the natural immune and the artificial immune theories, it described the idea of using the artificial immune technique in e-commerce personal recommendation, and gave the explaining method for recommender technique and its problems with the shape-space model. The clustering immune network recommendation algorithm was given. Experimental result shows that the proposed algorithm can solve the recommender problem more highly and efficiently, and has the advantage of good application value.