Construction of Intelligent Recommendation Retrieval Model of FuJian Intangible Cultural Heritage Digital Archives Resources

作     者：Xueqing Liao 

作者机构：Quanzhou University of Information EngineeringSchool for Creative StudiesQuanzhouFujian362000China 

出 版 物：《Intelligent Automation & Soft Computing》 (智能自动化与软计算（英文）)

年 卷 期：2023年第37卷第7期

页      面：677-690页

核心收录：

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Knowledge map intangible cultural heritage digital archives intelligent recommendation search TG-LDA model fasttext model 

摘      要：In order to improve the consistency between the recommended retrieval results and user needs,improve the recommendation efficiency,and reduce the average absolute deviation of resource retrieval,a design method of intelligent recommendation retrieval model for Fujian intangible cultural heritage digital archive resources based on knowledge atlas is *** TG-LDA(Tag-granularity LDA)model is proposed on the basis of the standard LDA(Linear Discriminant Analysis)*** model is used to mine archive resource *** Pearson correlation coefficient is used to measure the relevance between *** on the measurement results,the FastText deep learning model is used to achieve archive resource *** to the classification results,TF-IDF(term frequency–inverse document frequency)algorithm is used to calculate the weight of resource retrieval keywords to achieve resource retrieval,and a recommendation model of intangible cultural heritage digital archives resources is built through the knowledge map to achieve comprehensive and personalized recommendation of *** experimental results show that the recommendation and retrieval results of the proposed method are more in line with users’needs,can provide users with personalized digital archive resources,and the average absolute deviation of resource retrieval is low,the recommendation efficiency is high,and the utilization effect of archive resources is effectively improved.