Research On The Intelligent Search Service Model Of University Libraries Based On Big Data

With the steady growth of virtual content and virtual digital library users,the availability of search services on websites is becoming increasingly important to provide effective services for scientific navigation and access to key resources.As an important source of information for university students and faculty to conduct scientific research,it is necessary for university library search services to innovate technology in response to users' changing resource retrieval needs.In order to respond to the changing user needs,intelligent,digital and dynamic university library intelligent search service has become an inevitable development trend.This paper explores the intelligent search service model of "double first-class" university libraries with the help of advanced technology concept of big data,which has implications for the development of library services.The main work of the paper is as follows.(1)An empirical research was conducted on 35 "double first-class" university libraries in China.From the results of the survey,it can be found that the search service on the homepage of each university library is in the transition period to the direction of intelligent search service,and the overall development trend is good.With the core of satisfying users' resource search needs and the academic search engine as the guide,more diversified search services are presented.The services are more intelligent,humanized,precise and dynamic,and the achievable functions are increasing,using more advanced technologies and setting up richer columns.In general,the active exploration of intelligent search services by university libraries is a noteworthy and correct development direction.At the same time,some shortcomings were found during the research,such as the search engine's functions are not perfect,readability is not strong enough,and it is not yet up to the degree of dynamic intelligent recommendation.(2)A holistic construction of the intelligent search service model of university libraries based on big data was carried out,combining theoretical research and practical investigation,using the technology and ideas of big data as a guide,and designing the general framework of the model.Four sub-models of the smart search service model were constructed from four aspects,namely,smart retrieval service based on mobile visual search,smart recommendation service based on user behavior analysis,smart interaction service based on user interaction,and smart guidance service based on user needs,respectively.(3)The library of Peking University,which is prominent in the design of smart search services,is selected as the case study of this paper,and the contents of smart search services provided by its library homepage,We Chat public number and other platforms are studied.With this case study,we summarize the problems in the intelligent search services of most university libraries in China and put forward reasonable suggestions.The research on smart search service of university libraries has important theoretical and practical significance: in theory,it provides a new guiding direction for the operation of the search service mode of smart libraries,and in practice,it provides certain reference for the future development trend by combining the current situation of smart search service.