多Agent协同的电子商务推荐系统模型

为了进一步提高电子商务推荐系统中商品推荐的准确性和高效性，通过分析传统推荐系统存在的问题和已有的优化方案，提出了多Agent的电子商务推荐系统模型。推荐系统通过人工智能领域中的多Agent技术，并应用终端自适应特性，改善了传统推荐系统在多终端情况下的电子商务系统的推荐效率，并根据用户使用的不同终端动态返回推荐结果。实验结果表明，多Agent协同的电子商务推荐系统在一定程度上提高了推荐效率和准确性。

Multi-Agent cooperative E-commerce recommender system model

In order to further improve the accuracy and efficiency of product recommendation in E-commerce recommender system, by analyzing the problems of traditional recommender system and prior optimization technique, a multi-Agent recommender system model was proposed. By adopting multi-Agent technique in Artificial Intelligence (AI) and terminal self-adaption, this model improved the efficiency of traditional recommender system in the condition of using multi-terminal, and dynamically returned recommendation to users according to different terminals. The experimental results show that multi-Agent cooperative E-commerce recommender system improves the accuracy and efficiency to a certain extent.