摘要
为了研究动态数据下的TextRank与用户情感倾向在推荐算法中的应用,本文在TextRank算法进行细致分析的基础上,结合动态数据的时效性特点进行了综合改进,结合时间衰减参数与时效性参数TL,将原本单一的PR值变为了综合PR值,实验结果证明,综合PR值相比于原PR值是更加合理的。在此基础上,利用综合PR值数据与用户自身的静态数据以及用户情感倾向进行整合,通过推荐算法的综合筛选,得出最终的推荐结果,为用户提供了一个良好的体验。
In order to study the application of TextRank under dynamic data and user sentiment in the recommendation algorithm,a comprehensive improvement was made based on the detailed analysis of the TextRank algorithm,combined with the timeliness characteristics of dynamic data,combined with time attenuation parameters and timeliness parameters TL,The original single PR value is changed to a comprehensive PR value.The experimental results prove that the comprehensive PR value is more reasonable than the original PR value.On this basis,the comprehensive PR value data is integrated with the user's own static data and the user's emotional tendency,and the final recommendation result is obtained through the comprehensive screening of the recommendation algorithm,providing a good experience for the user.
作者
齐平平
QI Pingping(School of Communication and Electronic Engineering,East China Normal University,Shanghai,200241 China)
出处
《科技创新导报》
2021年第11期159-161,165,共4页
Science and Technology Innovation Herald
