人工免疫系统中个体间交互作用对推荐社区的影响
On the Effects of Idiotypic Interactions for Recommendation Communities in Artificial Immune Systems
摘要：
之前已经证明，基于免疫系统独特型原则的推荐器可以胜过仅基于相关性的推荐器。本文报告的工作正在进行中，我们进行了一些调查的性质，这种有益的影响的结果。最初的研究结果是，免疫系统推荐往往会产生不同的邻居，这种推荐的优越性能部分是由于不同的邻居，部分是由于独特型效应被用来加权每个邻居的建议。
英文摘要：
It has previously been shown that a recommender based on immune system idiotypic principles can out perform one based on correlation alone. This paper reports the results of work in progress, where we undertake some investigations into the nature of this beneficial effect. The initial findings are that the immune system recommender tends to produce different neighbourhoods, and that the superior performance of this recommender is due partly to the different neighbourhoods, and partly to the way that the idiotypic effect is used to weight each neighbours recommendations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
