This
paper discusses the personalized service processing methods of university
libraries, and proposes implementation methods, demand analysis and
personalized service forms for university libraries based on data tracking
technology. This paper uses big data behavior tracking and other technologies
to analyze and track the user behavior information of user groups in Chinese
university libraries through the Internet, find the points of interest to
users, and then make point-to-point service recommendation. Through the
investigation and analysis of a large number of library user demand data,
personalized services are provided from the aspects of library personalized
reading, book classification recommendation, personalized book evaluation technology
design, etc. The construction of the reading service platform plays a positive
role in demonstration and guidance.
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