基于页面的用户偏好协同过滤算法研究

Based on the page the user preference research on collaborative filtering algorithin

本文针对传统的协同过滤推荐算法存在的影响推荐质量的数据稀疏性问题和实用准确性问题,设计了一种基于页面的用户偏好协同过滤算法,并通过实验验证了该算法在数据稀疏性等方面均优于传统算法。

According to the traditional collaborative filtering algorithms existing recommendation quality data sparsity problem and practical problem of accuracy, based on the design of a page to the user preference collaborative filtering algorithm, and the experimental verification of the algorithm in data sparseness is better than the traditional algorithm.