Research On Accurate Digital Reading Recommendation Of University Libraries Enabled By Artificial Intelligence

With successful use of artificial intelligence technology to health care,finance,agriculture,urban management,and many other areas,the library as a fusion of emerging technology innovators,in the face of growing personalized reading preferences,at this stage,it is possible to carry out accurate recommendation services for digital reading with the help of artificial intelligence technology,so as to further improve the quality of the library’s reader service and enhance the library’s authority in readers’ ideas.This paper selects the domestic 31 "double first-class" university library as the research object of digital reading accurate recommendations,the university library is a school of literature information resource center,not only the basis of digital reading resources construction condition is good,and need the service of readers are numerous teachers and students,and is suitable to carry out research in digital reading accurate recommend object.By investigating the current situation of accurate digital reading recommendation service of 31 sample university libraries,the basic situation of their recommended reading objects,recommended reading resources and recommended reading channels is understood.After analyzing the current situation,four major problems existing in accurate digital reading recommendation service of university libraries are obtained.Fuzzy positioning of recommendation objects hinders accurate identification of reader groups,cumbersome acquisition of recommendation resources affects accurate matching of reading resources,blocked communication of recommendation channels restricts accurate push of recommendation information,and lack of construction of recommendation scenes limits accurate feedback of recommendation services.In view of the problems found after investigation and analysis,this paper believes that university libraries can use artificial intelligence technology to solve these problems.The main optimization path is divided into two parts: optimization strategy and safeguard measures.Optimization strategy including smart mining recommend readers demand support object accurate identification,establish intelligent warehouse help recommend resources accurate matching,recommend service channels intelligent linking to promote information precision push,building intelligent interaction scenarios help recommend service accurate feedback,so as to realize every reader can experience with personalized digital reading accurate recommendation service.Safeguard measures include cooperating with AI enterprises to build,share and improve the intelligent recommendation platform,upgrading the data security in the library with the latest AI support technology,building AI intelligent librarian team to achieve accurate recommendation effect,and ensuring the stable operation of digital reading accurate recommendation service system based on artificial intelligence technology.The innovation of this paper is to study the digital reading recommendation service of university libraries from the perspective of artificial intelligence.The results and recommendation service four aspects put forward targeted optimization strategies,and at the same time put forward relevant operational guarantee measures,explore and construct the system construction logic of the digital reading accurate recommendation service in university libraries,and provide suitable digital reading recommendation services for different readers.It has strong theoretical significance and practical value for solving related problems of library digital reading recommendation,and provides theoretical reference and practical solutions for library digital reading recommendation.