Research on the Intelligent Consulting Service Model of University Library in the Network Environment
In the process of intelligent development of university libraries,relying on a simple digital consultation model only enables passive static services,resulting in a lower hit rate(HR)of consultation service outcomes.Therefore,a new intelligent consultation service model for university libraries is proposed in the network environment.By aggregating a large amount of consultation records data from university libraries and utilizing the concepts of knowledge graph,a systematic treatment is applied to establish a knowledge base in the field of intelligent consultation services.Based on user behavior data and consultation records,the user's consultation needs are pro-actively sensed and accurately expressed.A smart question-answering service system is built on the foundation of Convolutional Neural Network(CNN)with attention mechanisms,to deeply learn and find corresponding answers from the knowledge base.Finally,by combi-ning user profile,library resource profile,and contextual profile,personalized intelligent push services are provided to consulting users.Application analysis results demonstrate that the researched consultation service model achieves a hit rate of over80%,effectively meet-ing the requirements of intelligent development in university libraries.
NETL
NSTL
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