基于LDA与双向GRU的借阅主题热度预测  

Prediction of Book Borrowing Topic Heat Based on Latent Dirichlet Allocation and Bidirectional Gate Recurrent Unit

作　　者：陈志辉 吴克晴[1] 陈嘉超 秦泽豪 CHEN Zhihui;WU Keqing;CHEN Jiachao;QIN Zehao(College of Science,Jiangxi University of Science and Technology,Ganzhou 341000,China;College of Information Science and Engineering,Jiaxing University,Jiaxing 314000,China)

机构地区：[1]江西理工大学理学院,江西赣州341000 [2]嘉兴学院信息科学与工程学院,浙江嘉兴314000

出　　处：《软件导刊》2024年第7期51-57,共7页Software Guide

摘　　要：图书借阅主题分析能够挖掘读者借阅喜好和阅读规律,通过使用借阅主题热度预测模型能够预测读者借阅主题热度变化趋势,对图书馆开展阅读推广活动具有重要意义。为了解决图书借阅主题提取、主题热度预测问题,提出基于LDA与双向GRU神经网络的借阅主题热度预测模型。该算法通过LDA算法提取读者不同时间段中的借阅图书特征和借阅主题,在计算不同时间段借阅主题热度、构建借阅主题热度序列数据集的基础上,构造基于双向GRU神经网络的主题热度预测模型以预测未来主题热度变化趋势,并在厦门大学图书馆纸质文献借阅记录数据集上进行实验评估。实验结果表明,模型能准确获得借阅主题与关键词之间的关系,与机器学习等算法比较可知,该模型能有效降低借阅主题热度预测误差。The analysis of book borrowing theme can mine read borrowing preferences and reading rules of readers.By using the prediction model of borrowing theme heat,it can predict the change trend of borrowing theme heat,which is of great significance for libraries to carry out reading promotion activities.In order to solve the problem of book borrowing topic extraction and topic heat prediction,this paper proposes a borrowing topic heat prediction model based on LDA and bidirectional GRU neural network.The algorithm extracts the borrowing book features and borrowing topics of readers in different time periods through LDA algorithm.On the basis of calculating the heat of borrowing topics in different time periods and constructing the data set of borrowing topic heat sequence,a topic heat prediction model based on bidirectional GRU neural network is constructed to predict the change trend of future topic heat,and the experimental evaluation is carried out on the paper literature borrowing record data set of Xiamen University Library.The simulation results show that the model can accurately obtain the relationship between borrowing topics and keywords,and compared with algorithms such as machine learning,the model can effectively reduce the prediction error of borrowing topics.

关 键 词：热度预测 借阅主题发现 深度学习 双向门控循环单元 潜在狄利克雷分配 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]