Research on Personalized Recommendation of University Libraries Based on Big Data
In recent years,the rapid development of big data and cloud computing technology,In-ternet of Things technology,and artificial intelligence algorithms has provided support for intel-ligent book resources and database table classification management in university libraries.Librar-ies in various regions rely on B/S(Browser/Server)browsers/servers,SOA(Service Oriented Architecture)master-slave service architecture,SQL Server databases,backend servers,and other software and hardware to construct smart book service systems that cover book retrieval,book borrowing,reading recommendations,book or literature downloads,etc.Based on this,the Ha-doop distributed software framework,HDFS file system,MapReduce programming model,Hbase database,Hive data warehouse and other software and hardware are introduced to con-struct an intelligent service system for resource scheduling and management in university librar-ies.Based on the book reading self portraits of different reader users,K-Means unsupervised clustering algorithm,Apriori association rule mining technology and other big data technologies are used to crawl and mine popular and personalized books in the library,complete intelligent book resource retrieval and personalized book recommendation,and improve the quality of in-telligent service and management in university libraries.
Big dataUniversity librariesPersonalized recommendationsResearch
万方数据
维普
