基于泛函网络的组合推荐算法

在研究组合算法的基础上，提出一种基于泛函网络实现前融合推荐算法. 探讨Vague集条件下推荐算法的前融合问题，给出了基于泛函网络构架实现前融合组合推荐算法的一般过程. 通过推荐系统泛函拓朴结构的建立，利用泛函神经元的自学习、自组织和自适应能力，进一步优化推荐结果，较大地提高了系统的推荐准确度. 最后，将算法应用于Movielens推荐系统中，计算机仿真实验结果表明，本文提出的基于泛函网络实现前融合推荐算法是有效的、可靠的.

Hybrid recommendation based on functional network

Based on the research of hybrid recommendation, model hybrid recommendation algorithm is provided with functional network. Meanwhile, how to get the model hybrid recommendation with vague set is discussed, so the general process of model hybrid recommendation using functional networks is studied. The topology of a functional network is established to improve the accuracy of the system's recommendation by using the neuron's self-learning, self-organizing and adaptive ability. Finally, the algorithm is used in Movielens recommender system. Computer simulation and experimental results show that the algorithm is effective and reliability.