基于协同过滤算法的大数据信息推荐模型

Big Data Information Recommendation Model Based on Collaborative Filtering Algorithm

针对传统大数据信息推荐模型存在匹配度低、用户满意度低的问题,笔者提出基于协同过滤算法的大数据信息推荐模型。经过信息协同过滤,根据用户对大数据信息的个性化需求偏好,得到关键词矩阵,对于更新后的大数据信息,利用规范化处理后的推荐模型实现大数据信息推荐。实验结果表明,设计方法在匹配度和用户满意度方面具有比较好的推荐效果。

Aiming at the problems of low matching degree and low user satisfaction in traditional big data information recommendation models,a big data information recommendation model based on collaborative filtering algorithm is proposed.After information collaborative filtering,a keyword matrix is obtained according to the user's personalized demand preference for big data information.For the updated big data information,the standardized processing recommendation model is used to realize the recommendation of big data information.The experimental results show that the design method has a relatively good recommendation effect in terms of matching degree and user satisfaction.