基于内容过滤的农业信息推荐系统

摘要

To realize the personalized recommendatory service effectively, the content-based filtering recommendatory technology is adopted in the design process of the agriculture information recommendation system. A new user comprehensive interest model is presented. The model can calculate the similarity of user and the document by the synthetically weights of background, reading and operation behavior factors of users, and recommend document to users based on this. By the practical tests, the results show that increasing the weights of user's reading and operating behavior in model can effectively improve the recommended precision.%针对如何有效实现个性化推荐服务的问题,在农业信息推荐系统的设计过程中,采用基于内容过滤的推荐技术,提出一种新的用户综合兴趣模型.模型通过将用户背景、阅读与操作行为等因素进行综合加权,计算用户与文档的相似度,并以此向用户推荐文档.测试结果表明,提高用户阅读与操作特征在模型中所占的权重,可以有效提高推荐精度.